Deep Learning in Image Processing and Segmentation

Dear Colleagues,

Image processing has been traditionally attempted using number of approaches that have been vital for the growth of computer vision. The applications that have emerged from such traditional approaches have changed the way we live, from vehicle number plate recognition to medical imaging, and without the growth of image processing, our modern lives will cease to exist. The traditional image processing tasks involve:

• Image enhancement;
• Image restoration;
• Wavelets and multi-resolution processing;
• Image compression;
• Morphological processing;
• Representation and description;
• Object detection and recognition;
• Knowledge base.

Image segmentation is also one of these image processing tasks; however, this journal Special Issue will treat these two sections separately as it wants to discover the new trends in these two traditional fields using deep learning or artificial intelligence-based approaches. This volume calls for recent research progress using deep learning in realizing the above image processing tasks or approaches that would result in image segmentation similar to traditional watershed algorithms, region-growing algorithms or any modern approaches.

Dr. Prashan Premaratne
Guest Editor

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