Abstract
The rational field is highly desired in many applications. Algorithms using the rational number field algebraic number fields use only integer arithmetics and are easy to implement. Therefore, studying and designing systems and expansions with coefficients in or algebraic number fields is particularly interesting. This paper discusses constructing quasi-tight framelets with symmetry over an algebraic field. Compared to tight framelets, quasi-tight framelets have very similar structures but much more flexibility in construction. Several recent papers have explored the structure of quasi-tight framelets. The construction of symmetric quasi-tight framelets directly applies the generalized spectral factorization of matrices of Laurent polynomials with specific symmetry structures. We adequately formulate the latter problem and establish the necessary and sufficient conditions for such a factorization over a general subfield of , including algebraic number fields as particular cases. Our proofs of the main results are constructive and thus serve as a guideline for construction. We provide several examples to demonstrate our main results.
Keywords:
generalized matrix spectral factorization; quasi-tight framelets; framelet filter banks; symmetric framelets MSC:
42C40; 42C15; 41A15; 65D07
1. Introduction
1.1. Backgrounds
In many science and engineering applications, people often digitalize data and use particular devices to process and analyze them. Quite commonly, data are stored in integers or rational numbers for machine processes, such as an 8-bit grayscale image or audio in a digital recorder. Therefore, the rational field , or any of its finite extensions (also known as algebraic number fields), are desired in many scientific computing applications. Implementing algorithms using algebraic number fields is quite efficient since only integer arithmetics are involved. Consequently, studying and designing systems and expansions over algebraic number fields is of great interest.
Over the past decades, wavelets and framelets have been extensively studied and applied in numerous applications, such as signal processing and numerical algorithms. Several excellent properties, such as sparse multi-scale representations and fast discrete transforms, make wavelets and framelets perform well in the applications above. As a generalization of wavelets, framelets not only preserve almost all the good properties of wavelets but also offer the new feature of redundancy, which gives framelets robustness under data corruption or quantization. Over the past few years, framelets with attractive properties, such as symmetry and high-order vanishing moments, have been well-investigated (see e.g., [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23]). One of the fascinating topics is to design symmetric (or anti-symmetric) framelets (or framelet filter banks) whose coefficients belong to or an algebraic number field. The properties and examples of such framelets have been extensively explored in papers such as [2,8,11,15,16,24,25,26].
Motivated by the work described above, in this paper, we focus on (dyadic) quasi-tight framelets with coefficients over an algebraic number field. The notion of a quasi-tight framelet generalizes a tight framelet. It is well-known that a tight framelet filter bank is often derived from a refinement filter/mask that satisfies the sub-QMF condition. However, many refinement filters fail to meet the sub-QMF condition, and we cannot obtain a tight framelet filter bank in such cases. Therefore, we hope to obtain something similar to a tight framelet filter bank from an arbitrary refinement filter, thus motivating the introduction of a quasi-tight framelet filter bank. The notion of quasi-tight framelets was first introduced in [25] and was then investigated in several subsequent recent papers, such as [2,25,26,27]. Existing studies have demonstrated the advantages of quasi-tight framelets over tight framelets. On the one hand, quasi-tight and tight framelets behave almost identically. On the other hand, compared to tight framelets, quasi-tight framelets have much more flexibility and are much easier to construct. Therefore, it is natural and necessary to consider quasi-tight framelets. The main goal of this paper is to provide a characterization and, more importantly, algorithms for constructing quasi-tight framelets with symmetry and coefficients in an algebraic number field.
1.2. Generalized Matrix Spectral Factorization with Symmetry
The construction of a symmetric quasi-tight framelet filter bank is closely related to generalized matrix spectral factorization with symmetry. To properly formulate this problem, we must first introduce some notations and concepts.
Throughout this paper, is a field that satisfies
where denotes the complex conjugate of x. The condition (1) is mild and normal when constructing wavelet and framelet filter banks. The most commonly used fields and algebraic number fields, such as , all satisfy (1). A Laurent polynomial with coefficients from a field takes the form
where its coefficient sequence has only finitely many non-zero terms (in such cases, we say that u is finitely supported) and for all . Denote , the set (ring) of all Laurent polynomials with coefficients in . Throughout this paper, we use the sans serif font style letters to denote (matrices of) Laurent polynomials and the normal/regular font style letters to denote the corresponding coefficient sequence of the Laurent polynomial.
We say that has symmetry if
for some and . It is trivial to see that (2) is equivalent to
If is not the zero polynomial and has symmetry, we define
The operator is known as a symmetry operator in wavelet and framelet analysis. Denote , the set of Laurent polynomials with symmetry and coefficients in . It is easy to see that (2) holds if, and only if, is a monomial. For , we call the monomial the symmetry type of . For convenience, if is the zero polynomial, then has any symmetry type.
Let be a matrix of Laurent polynomials, where for all , we define the Hermitian conjugate of via
When is a matrix, that is, is a Laurent polynomial, then the Hermitian conjugate is just the conjugate of for all . In this case, we denote . Note that if , then . For an matrix of Laurent polynomials, we say that is Hermitian if . If all entries of have symmetry, then we can define its symmetry type . For a matrix whose entries are Laurent polynomials in , define the matrix of monomials through for all and .
Next, we discuss how the symmetry property behaves under matrix operations. Let , , and be , , and matrices of Laurent polynomials in . We have the following definitions:
- If , then have symmetry with
- We say that the symmetry type of is compatible or has compatible symmetry ifholds for some and row vectors of Laurent polynomials and with symmetry. For convenience, denote , the set of all matrices with entries in and have compatible symmetry.
- We say that the multiplication is compatible iffor some , , and row vectors , , and of Laurent polynomials in . It is obvious that in this case, has compatible symmetry with
We are ready to formulate the generalized matrix spectral factorization problem with symmetry. Let be such that and for some vector of Laurent polynomials with symmetry. By , we mean the diagonal matrix whose diagonal elements are (ordered) . A generalized spectral factorization of with symmetry over the field is of the form
where , for some with , , and all multiplications in (6) are compatible. When the underlying field , then we may choose , which is the identity matrix and thus (6) reduces to
In particular, we are interested in the case when because it is related to constructing (dyadic) quasi-tight or tight framelet filter banks with two generators that we will discuss later. In this case, the generalized spectral factorization becomes
for some and .
1.3. Related Work
When in (7), the factorization is known as a spectral factorization of . The spectral factorization problem and the construction of tight framelets have been well-investigated in several pieces of work. For instance, refs. [6,9] studied the case when ; ref. [15] addressed the case when and specifically studied how to construct tight framelets with rational coefficients; ref. [16] investigated the case when is any field that satisfies (1). If we drop the symmetry requirements of in (7) and let , then we have the well-known matrix Fejér–Riesz lemma (see [28]) in the literature.
On the other hand, the case when in (7) is much more complicated and different from the case , as we no longer have the positive semi-definite property for all . Some recent related papers, such as [2,26], investigated (7) with or without symmetry for the case when and . Our goal is to complete the picture of the generalized spectral factorization problem by resolving the unsolved general case when is an arbitrary field that satisfies (1).
1.4. Our Contributions and Paper Structure
Here, we summarize our contributions. First, we completely solve the generalized spectral factorization of matrices with symmetry over a general subfield of that is closed under complex conjugation. In particular, we are interested in Hermitian matrices with symmetry type , as these matrices are particularly concerned with framelet constructions. We establish the necessary and sufficient conditions for such a matrix to admit a factorization as in (7) with . Next, we apply the theory of generalized spectral factorization to construct symmetric quasi-tight framelets with two generators. We consider how to derive the high-pass filters with symmetry and coefficients in an algebraic number field from a refinement filter a that fails to satisfy the sub-QMF condition. Moreover, our construction guarantees that the high-pass filters achieve the highest possible order of vanishing moments.
The paper is organized as follows: In Section 2, we establish the first main result Theorem 1 on the generalized spectral factorization of matrices with symmetry over a general field that satisfies (1). Our proof is constructive and thus can serve as a factorization algorithm. Next, in Section 3, we briefly review the basic concepts of framelets and demonstrate the connection between constructing quasi-tight framelets and the generalized spectral factorization. Then, we apply the results from Section 2 to deduce our second main result Theorem 3 on constructing quasi-tight framelets with symmetry and coefficients over the general field . Finally, Section 4 provides several examples of quasi-tight framelets with symmetry.
2. Generalized Spectral Factorization with Symmetry over Algebraic Number Fields
In this section, we establish the first main result of the paper on generalized matrix spectral factorization of Laurent polynomial matrices with symmetry over a field that satisfies (1).
For simplicity, define
Any is Hermitian and has compatible symmetry. Here is the main theorem on the generalized spectral factorization with symmetry over :
Theorem 1.
Let be such that for some and . Suppose , then the following two statements are equivalent:
- (1)
- for some with and some ;
- (2)
- there exist and for some with such thatand the symmetry type of satisfies
Proof.
(2) ⇒ (1): Suppose (2) holds, then take and , we have item (1).
(1) ⇒ (2): Suppose (1) holds, then a desired matrix factorization of that satisfies both (8) and (9) can be obtained by performing the following steps:
- Step 1. Construct and such that
- (i)
- ;
- (ii)
- for some ;
- (iii)
- and all multiplications are compatible.
- Step 2. Construct and such that
- (i)
- ;
- (ii)
- and all multiplications are compatible.
- Step 3. Construct and with and such that and all multiplications are compatible.
The justifications of Steps 1–3 are long and technical, so we postpone them to later subsections. Once we have finished the above three steps, define and let be the same as in Step 3; all claims of the item (2) follow immediately. The proof is complete. □
Remark 1.
To obtain a generalized factorization, we need to shrink the length (see the definition in Section 2.1) of . More specifically, we need to find a matrix whose determinant is a constant and so that with all multiplications being compatible. For the case when , which has been studied in [2], the approach of [2] to achieve this relies on a matrix normal form with compatible symmetry (see [Theorem 3.9 [2]]) and splitting into a product of linear factors over (see [Lemma 3.12 [2]]). Some linear factors of are used to construct a desired matrix that help shrink the length of . However, we cannot adopt the same approach to the general case (i.e., when is an arbitrary subfield). When such that is an arbitrary subfield and is a linear factor of , then it may happen that . As a result, to ensure that all entries of have coefficients in , we cannot use the if it is not in . When working on the proof of Theorem 1, everything (e.g., factorizing polynomials) must be performed over , not , which is why difficulties arise. Consequently, we provide a new approach that consists of steps 1 and 2 in our proof, in which we show some new techniques.
When factorizing the matrix in Step 3, several steps involve taking square roots of numbers to obtain the matrix as required. For the case when , there is no problem because is closed under taking square roots. But for a general subfield of , we must be careful with this as we have to ensure that all entries of are in . Therefore, though we can borrow some ideas from [2] to justify Step 3, our proof will have new elements and tools to overcome the difficulties of taking square roots.
2.1. On the Symmetry Property of Laurent Polynomials
Before we justify steps 1–3, let us review some important facts about the symmetry property of Laurent polynomials.
For , define
- the lower degree of by
- the degree of by
- the length of by
The following proposition can be verified by direct computation:
Proposition 1.
Suppose such that and for some and . Then,
- (1)
- if , then with ;
- (2)
- with ;
- (3)
- if divides , then with ;
- (4)
- with
If in addition , then , , and , where is defined for every as
To characterize the symmetry property of a Laurent polynomial, we need to analyze the multiplicities of its roots. Denote the multiplicity of the root of at . The following result is well-known (see e.g., [Proposition 2.2 [6]] and [Lemma 3.2 [2]]).
Lemma 1.
Let .
- (1)
- if, and only if, for all .
- (2)
- If is a non-zero Laurent polynomial with symmetry type for some and , then and .
Next, we discuss some properties of matrices of Laurent polynomials with compatible symmetry. Suppose that satisfies (5) for some and row vectors of Laurent polynomials and with symmetry. We can tell the symmetry relations between the rows and columns of from and :
For a matrix , we can prove by induction that with
If in addition is strongly invertible, that is, for some and , then . In this case, as , where is the adjugate matrix of , and
we see that and it has symmetry type
From the above discussion, if is strongly invertible, then for and , if the multiplication (resp. ) is compatible, then so is the multiplication (resp. ).
2.2. Justification of Step 1 in the Proof of Theorem 1
To find the desired matrices and in Step 1, we need to take out all the common divisors of the entries of . We first introduce the following lemma which generalizes [Lemma 3.15 [2]]:
Lemma 2.
Let be such that divides . Then, there exists such that
Moreover, for any that satisfies (14), we have for some .
Proof.
Define . By the assumptions on and , we have with . Suppose is an irreducible factor of that does not have symmetry. By the symmetry of , we see that is another irreducible factor of and is coprime to . Thus, divides . Moreover, divides or . By the symmetry of , we conclude that divides or and thus divides . By the choice of , we see that it does not divide . Consequently, divides .
From the above discussion, we can write
where and . By letting , we have and (14) holds.
Now, let be arbitrary such that (14) holds. Denote , and for some and . By Lemma 1, we have Moreover, by Proposition 1, we obtain
Therefore, we can find such that . □
Remark 2.
[Lemma 3.15 [2]] is a special case of Lemma 2 with . The original proof of [Lemma 3.15 [2]] relies on [Theorem 2.9 [6]] and is over-complicated from our point of view. Hence, we presented the above simpler self-contained proof.
Next, we have the following lemma that allows us to further take out the common factors of entries of . For , by , we mean the greatest common divisor of and in .
Lemma 3.
Let be such that for some and some with . Define and . If , then there exist that both divide and satisfy
for some and . Moreover, .
Proof.
Define . As all entries of have symmetry, so is . Moreover, we have . Thus by letting , we see that , and , where . Observe that divides and , so and are well-defined Laurent polynomials in .
We prove that
for some , and that divides . First, note that if , then , so and the claim clearly holds.
Now, assume . We first prove that . Let be an irreducible element such that divides both and . By the choice of , we see that divides and . Because is irreducible, we must have either or divides . Moreover, as and are Hermitian, both must be divisible by . Consequently, or divides all and . By the assumption , up to a monomial, we must have . Next, we show that if is irreducible and divides , then must divide . Indeed, if is an irreducible factor of , then by using a similar argument of the proof of the previous claim, either or divides and thus divides . On the other hand, as , we see that divides . Using the irreducibility of , we see that divides . Now, using the fact that and , we conclude that divides . Consequently, we have divides .
We now analyze the symmetry of the factors of . Let be an irreducible factor of that has no symmetry. Then, must be relatively prime to . By the definition of , we see that must divide or . Noting that has symmetry, we must have divides or and thus divides . Similarly, we have divides . As , we conclude that divides and thus divides . Consequently, we can write
such that , , and all . By letting , we have and . Observe that each polynomial in (17) either divides or . Therefore, without loss of generality, we may assume that all ’s divide . As a result, we have .
Similarly, we can show that there exists that divides and satisfies for some . Furthermore, by the choices of and the fact that , we must have .
Finally, by letting and , all claims of the lemma hold and the proof is complete. □
Remark 3.
Let be such that for some and with . Suppose , then by Lemma 3, we can define the following sets for convenience:
For any and , we have .
Now, we have all the tools to justify Step 1.
Justification of Step 1 in the Proof of Theorem 1.
As satisfies all assumptions of Lemma 3, we can define as in (18) and as in (19). Choose and . Define
It is trivial that satisfies item (i) in Step 1.
Next, we have ,
and
Thus, it is easy to see that item (iii) in Step 1 holds.
Finally, since
then by Lemma 2, there exists such that . This justifies item (ii) in Step 1. □
2.3. Justification of Step 2 in the Proof of Theorem 1
To justify Step 2, we need the following Euclidean algorithm compatible with the symmetry property. We have the following lemma, which is a straightforward generalization of [Theorem 3.9 [2]].
Lemma 4.
(Extended Euclidean Algorithm for Laurent polynomials in ). Let and define . There exist such that
Furthermore, and .
Justification of Step 2 in the Proof of Theorem 1.
Let and be the same as in Step 1. By Lemma 4, there exist such that
Define
Then, , and thus . Furthermore, direct calculation shows that
By letting
we have and . Moreover, the symmetry relations in (21) yields and . By calculation, we have
Therefore, , , and the matrix multiplications in are compatible. This completes the justification of Step 2. □
2.4. Justification of Step 3 in the Proof of Theorem 1
Justifying Step 3 is the most technical part of the proof of Theorem 1. Let be the same as in Step 2. The symmetry type of the entry is critical in justifying Step 3. Denote for some and . Consider the following two cases:
- Case 1. or and ;
- Case 2. and .
First, we work on the justification for case 1, which relies heavily on the long division with symmetry. We have two auxiliary lemmas.
Lemma 5.
Let be such that and . Then, there exist such that , and .
Proof.
Define , , and , so we write
where are coefficients for all and . Denote and for some and . It follows that
Define
Direct calculation yields
Therefore,
and thus . Moreover, by letting , it is trivial that and .
Next, we show that . As , we have . So and , which implies and . Hence, . Furthermore, observe that the coefficient of the term in is . This implies and thus . This completes the proof. □
Lemma 6.
Let be such that . Then, there exist such that ,
Moreover, if for all , then can be chosen such that .
Proof.
The case when is trivial, we just choose and . So, we assume that and the rest of the proof will be for this case.
We construct such that
Here is how such and are constructed:
- If , simply choose and .
- If , set . Starting from , whenever , apply Lemma 5 to find such that , and . As is finite, this iterative process must stop at some point. In particular, at some , we must have . DefineClearly . Moreover, by the definition of and above, together with the fact thatit is easy to see that and (22) holds.
If for some , then let and , we have , and (22) holds.
Suppose for all . Denote and for some and . We consider the following two cases:
- for some and : In this case, we must have . Then, by Proposition 1, we have and thus . Define and , where are defined as in (24). We see that (22) holds. Moreover, we have and thus it follows from Proposition 1 thatTherefore, and thus .
- for some : In this case, we have . Let be such that (23) holds. If , then simply let and , we see that and (22) holds. Otherwise, if , defineThen, it is trivial that . Writefor some coefficients for all and . DefineIt is trivial that , and the coefficient of the term in is . Therefore, we have , and thus . On the other hand, using Proposition 1, direct calculation yieldsBy letting , it is now straightforward to verify that and (22) holds.
The proof is now complete. □
Justification of Step 3 in the Proof of Theorem 1, Case 1.
There are two major steps in the constructions of and that are required:
- (SS1)
- Find such that is strongly invertible, has at least one zero entry, and all multiplications are compatible.
- (SS2)
- Factorize :such that , satisfy , and all matrix multiplications are compatible. By letting and , all claims of Step 3 hold.
We first justify (SS1). The case when has one zero entry is trivial; choose . So, we only need to justify the case when has no zero entry. Set . In this case, as is a constant and , we must have and . Therefore,
As a result, either or .
We now claim that there exists such that is strongly invertible, all multiplications in are compatible, and Let and suppose . As , we have . By the assumptions that or and , we can apply Lemma 6 to find such that , and . Define
In either case, is strongly invertible and with
for some with . Furthermore, we have
Therefore, , has symmetry type and thus all multiplications in (27) are compatible. This proves the claim.
If the matrix has one zero entry, then we just let , and go to step 2. Otherwise, apply the process in the above claim. To be specific, for , if has no zero entry, then construct such that is strongly invertible, all multiplications in are compatible, and By performing this iterative process, we obtain a sequence of matrices such that Hence, the sequence must have finite length; that is, the iterative process terminates at some , and has one zero entry. By letting
we have and is strongly invertible, and has one zero entry, and all multiplications above are compatible. This justifies (SS1).
Once we have obtained that has one zero entry, we move on to (SS2). Here, we consider three cases and define for each.
Define and . It is trivial that holds. Moreover, as the multiplications in are compatible and , we see that the symmetry type of can be written as for some vector of Laurent polynomials in . Therefore, by (13), we have , which implies that with symmetry type
Finally, observe that any constant diagonal matrix has symmetry type for any in the set above. This shows that all multiplications in are compatible and finishes the justification of (SS2). □
For case 2, the proof is much more tedious than case 1.
Justification of Step 3 in the Proof of Theorem 1, Case 2.
In either case, all multiplications are compatible. This completes the justification. □
First, consider the case when . Since with , it follows from Lemma 1 that , . This means has a factor . Furthermore, because and , we see that must divide or . Therefore, there exists such that , where or . Furthermore, and . Therefore, satisfies all assumptions of case 1, and all claims follow.
Now assume that . Observe that , as otherwise and thus is a non-zero monomial, which can never have symmetry type with . Now, we see from that for some . Let and be two Laurent polynomials in , where are some unknown parameters. Define . Using long division, there are such that
and . By setting , (28) induces a system of homogeneous linear equations with variables. Therefore, the set : (28) holds with has a non-zero element, say . By letting
we have
for some . By and , we deduce from (29) that
Define
Then, with
for some . Moreover, and are not both 0 and satisfy
It follows that
Since is a non-zero constant, we have . Thus, we conclude from the above calculation that divides . This means there exists with such that
Combining (31) and (32), we obtain the following technical identity:
With (33), we can now try to write all entries of in terms of and :
- and : By left multiplying to both sides of (33), we haveAs , we have divides . Recall that , it follows from the definition of that . Similarly . Hence,Moreover, it is easy to see from the symmetry types of and that . Therefore, and . Consequently, we must havefor some with , and it follows from (34) that
- Thus, .It follows that
Finally, define
It is trivial that . Furthermore,
- if , then
- if , then
3. Quasi-Tight Framelets with Symmetry
In this section, we apply the main result Theorem 1 to construct quasi-tight framelets with symmetry.
3.1. Basics on Framelets
We first recall some basic concepts and facts about framelets.
For , denote , the linear space of functions f that satisfies
When , the space is a Hilbert space with the following inner product:
Let be a function. For any real number c and any positive number , define
For , we say that is a framelet (i.e., a wavelet frame) in if there exist positive constants such that
For and , we say that is a quasi-tight framelet in if is a framelet in and
with the above series converging unconditionally in . It is well-known that (40) implies that is a homogeneous quasi-tight framelet in , that is,
with the above series converging unconditionally in . If in addition, , then is called a tight framelet in . In this case, is a homogeneous tight framelet in .
To reduce computational complexity in applications, we hope the framelet functions are compactly supported, and such framelets are often derived from compactly supported refinable functions from extension principles. To better discuss this in more detail, we introduce some notations here. First, for any integrable function , recall that its Fourier transform is defined via . The definition of the Fourier transform can be extended to functions and tempered distributions. Next, denote , the set (space) of all finitely supported sequences ; that is, every only has finitely many non-zero terms. For every , its symbol is the Laurent polynomial that is defined by
Suppose we have a finitely supported filter such that . It is well-known in wavelet and framelet theory that one can define a compactly supported distribution through
The distribution defined as (42) is called the standard refinable function associated with the finitely supported filter a, and we call a the refinement filter associated with . It is easy to verify that the following refinement equation holds:
To construct a compactly supported quasi-tight framelet, one can apply the unitary extension principle (UEP) (see e.g., [8,23,29,30]). Here, we state the quasi-tight framelet version of the UEP.
Theorem 2.
- (1)
- ;
- (2)
- there exist and finitely supported filters such that
- , where is the symbol of for all ;
- forms a quasi-tight framelet filter bank, i.e., the symbols satisfy
then, by letting
is a quasi-tight framelet in .
In a quasi-tight framelet filter bank , a is called the low-pass filter and are called the high-pass filters.
Let us make some comments on Theorem 2. First, to verify if defined in (42) is an element of , one can check the -smoothness exponent of the refinement filter a, denoted by . The quantity is technical; we refer the readers to [(5.6.44) [8]] for its definition and [Corollary 5.8.5 [8]] for the method to compute it. According to [Theorem 6.3.3 [8]], if , then
holds for every . In other words, belongs to the Sobolev space and thus .
Next, we see from Theorem 2 that the construction of a quasi-tight framelet essentially reduces to the design of an underlying quasi-tight framelet filter bank that satisfies (44) and (45). Define
To construct a quasi-tight framelet filter bank, it suffices to find and such that and
When , then (48) becomes a spectral factorization of the matrix . In this case, the refinement filter a necessarily satisfies the sub-QMF condition:
Unfortunately, many refinement filters fail to satisfy (49). For example, consider the refinement filter with
we have
Therefore, constructing a tight framelet is impossible in such cases, and we must work with the quasi-tight framelets. In fact, with the refinement filter a given in (50), we have the first observed example of a quasi-tight framelet filter bank in [Example 3.2.2 [8]].
3.2. Vanishing Moments and Symmetry
Two highly desired features for quasi-tight framelets are high-order vanishing moments and symmetry on the generators. Let us briefly discuss them here.
The orders of vanishing moments of the framelet generators reflect the sparsity of the framelet expansion (40). To better understand this, let us introduce some notations. For a finitely supported filter and , we say that
- u has order m sum rules iffor some Laurent polynomial . Denote with m being the largest positive integer such that (51) holds;
- u has order m vanishing moments iffor some Laurent polynomial . Denote with m being the largest positive integer such that (52) holds.
For a function , we say that has order m vanishing moments if
Denote with m being the largest positive integer such that (53) holds. Suppose is a quasi-tight framelet that is derived through the UEP from an underlying quasi-tight framelet filter bank . It is easy to show from (44), (45) and the definition of in (46) that
where is the filter whose symbol is given by
We always try to make as large as possible.
On the other hand, the symmetry of the framelet generators is critically important in handling boundary artifacts in many applications. To derive a symmetric quasi-tight framelet, we start with a refinement filter such that and . Then, the matrix defined in (47) is an element of . To construct the high-pass filters with symmetry, we must find a generalized matrix spectral factorization of as in (48) and ensure that all multiplications preserve the symmetry structure. It is well-known that a framelet filter bank with symmetry necessarily has high-pass filters. Quite often, we hope to have fewer high-pass filters in a framelet filter bank to make algorithms using framelet transforms efficient. For the construction of symmetric tight framelet filter banks, we refer the readers to [1,7,10] for the construction of symmetric tight framelet filter banks with and [6,9] for symmetric tight framelet filter banks with . The construction of symmetric quasi-tight framelets is much less investigated. To the best of the author’s knowledge, [2] is the only existing paper that studies symmetric quasi-tight framelets but with coefficients in the field .
3.3. The Main Theorem
From the previous discussion, we see that the smaller the number of generators is, the better. Therefore, we focus on symmetric quasi-tight framelet filter banks with two generators. Specifically, we work on characterizing and designing a quasi-tight framelet filter bank such that , for some and with . Moreover, we want our high-pass filters to have the highest possible order of vanishing moments. The construction of such a quasi-tight framelet filter bank will directly apply Theorem 1.
Before we present our main theorem, let us provide a brief guideline on constructing a quasi-tight framelet filter bank . Let be such that and . Define as in (47). To derive a quasi-tight framelet filter bank with high-order vanishing moments, it suffices to find such that
and is as large as possible. Choose with , , where is defined as in (54). Define
By the choice of n, it is easy to see that all entries of are Laurent polynomials in and . Define
Then, we have and , where is defined as in (47). Note that
from which it is not hard to see that Therefore, we conclude that
For any Laurent polynomial , define via
It is trivial to see that
Define
It is easy to verify that
Now, to construct a quasi-tight framelet filter bank , it suffices to find a matrix of Laurent polynomials in and a diagonal matrix for some with such that . Once this is done, define via
then it is easy to verify that is a quasi-tight framelet filter bank such that . Moreover, by letting
we have and for .
Theorem 3.
Let be such that and with for some . Let be such that where is defined as in (54). Define as in (56) and as in (60). The following statements are equivalent:
- (1)
- for some and with ;
- (2)
- there exist such that
- (i)
- is a quasi-tight framelet filter bank;
- (ii)
- and for some and with ;
- (iii)
- .
Define for all . If in addition , define
then is a quasi-tight framelet in such that all have symmetry and .
Proof.
(2) ⇒ (1): Denote where and for . We first show that . Assume otherwise, say . Since is a quasi-tight framelet filter bank, we have
As , and , we conclude that , which is a contradiction. Therefore, cannot happen. Similarly and cannot happen either. Consequently, we must have .
By items (ii) and (iii), there exist such that
and for . Define . As is a quasi-tight framelet filter bank, it is easy to derive from (55) that
where is defined as (56). Now, let be the same as in (61), we have
where
We show that . Consider the following two cases:
- : In this case, we have . Thus, and direct calculation yieldsTherefore, and thus .
- It follows that and thus with .
Now, by letting and , we see that item (1) holds.
(1) ⇒ (2): Define as in (57) and as in (58). Write as in (60). By (61) and the fact that , it is not difficult to see that .
By the symmetry type of , we have and . Consider the following two cases:
- : In this case, we have . Define and . Direct calculation yields whereUsing (59) and the definition of in (60), we see that . Hence, . Moreover, since , we see that . Therefore, satisfies all assumptions of Theorem 1, and thus there exist and with such thatandIt follows thatwhere . Now, define via (62) and via (63). It is clear that items (i) and (iii) hold. Moreover, direct calculation yieldsTherefore, using (67), we conclude that with and . This proves item (ii).
To this end, we have finished the proofs of (i)–(iii) in item (2).
If in addition , where , define and as in (64). It follows from Theorem 2 that is a quasi-tight framelet in . Moreover, we have . Finally, the symmetry of and follows immediately from the symmetry of and . □
4. Illustrative Examples
This section presents several examples to illustrate our main theorems on the generalized spectral factorization and quasi-tight framelets with symmetry.
Example 1.
Let and consider the refinement filter with
Define as in (54). We have , and . Let , define via (56) and via (60). Specifically, we have
and
Hence, by Theorem 3, we obtain a quasi-tight framelet filter bank such that have symmetry and at least order 1 vanishing moments.
We follow the steps in the proof of Theorem 1 to factorize :
- Step 1.
- Note that , so the entries of are already mutually coprime and we move on to step 2.
- Step 2.
- Define . Clearly . Moreover, by lettingWe have and .
- Step 3.
- Note that , so we follow the justification of step 3 for case 1 and defineThen, and thus . Moreover, we have .
Define
We see that and thus . Moreover, we have . Finally, derive the high-pass filters via (62) with and , we have
Note that and .
Example 2.
Let and consider the refinement filter with
Define as in (54). We have , and . Let , define via (56) and via (60). Specifically, we have
where
Note that
Hence, by Theorem 3, we obtain a quasi-tight framelet filter bank such that have symmetry and at least order 4 vanishing moments.
We follow the steps in the proof of Theorem 1 to factorize :
- Step 1.
- Note that , so the entries of are already mutually coprime and we move on to step 2.
- Step 2.
- Define whereWe have and thus . Moreover, we have and .
- Step 3.
- Note that , so we follow the justification of step 3 for case 1 and definewhereThen, and thus . Moreover, we have.
Define
we see that and thus . By letting = , we have . Finally, derive the high-pass filters via (62) with , and , we have
Note that , and .
Example 3.
Let and consider the refinement filter with
Define as in (54). We have , and . Let , define via (56) and via (60). Specifically, we have
where
Note that
Hence, by Theorem 3, we obtain a quasi-tight framelet filter bank such that have symmetry and at least order 3 vanishing moments.
We follow the steps in the proof of Theorem 1 to factorize :
- Step 1.
- Note that , so the entries of are already mutually coprime and we move on to step 2.
- Step 2.
- Define , whereWe have and thus . Moreover, we have and .
- Step 3.
- Note that , so we follow the justification of step 3 for case 2 and definewhereThen, and thus . Moreover, we havewhereNote that .
Define , where
We see that and thus . By letting , we have . Finally, derive the high-pass filters via (62) with , we obtain a quasi-tight framelet filter bank such that , and .
Funding
This research was funded by the National Natural Science Foundation of China under grants 12201178 and 12271140.
Data Availability Statement
Data is contained within the article.
Conflicts of Interest
The author declares no conflicts of interest.
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