Jayanta Mukhopadhyay

The textbook is primarily written for senior undergraduate and post graduate students studying in areas of computer science and engineering, and electrical engineering. However, as the subject covers various interdisciplinary areas, the book is also expected to be of interest to a larger readership in Science and Engineering. It has a comprehensive and balanced coverage of theory and applications of computer vision with a textbook approach providing worked out examples, and exercises. It covers theory and applications of some relatively recent advancements in technology such as on colour processing, deep learning techniques for processing images and videos, document processing, biometry, content based image retrieval, etc. It also delves with theories and processing in non-optical imaging systems, such as range or depth imaging, medical imaging and remote sensing imaging.

This book discusses different types of distance functions defined in an n-D integral space for their usefulness in approximating the Euclidean metric. It discusses the properties of these distance functions and presents various kinds of error analysis in approximating Euclidean metrics. It also presents a historical perspective on efforts and motivation for approximating Euclidean metrics by digital distances from the mid-sixties of the previous century. The book also contains an in-depth presentation of recent progress, and new research problems in this area.

Exploring theories and applications developed during the last 30 years, Digital Geometry in Image Processing presents a mathematical treatment of the properties of digital metric spaces and their relevance in analyzing shapes in two and three dimensions. Unlike similar books, this one connects the two areas of image processing and digital geometry, highlighting important results of digital geometry that are currently used in image analysis and processing. The book discusses different digital geometries in multi-dimensional integral coordinate spaces. It also describes interesting properties of the geometries, including metric and topological properties, shapes of circles and spheres, proximity to Euclidean norms, and number theoretic representations of geometric objects such as straight lines and circles. The authors—all active researchers in image processing and digital geometry—demonstrate how these concepts and properties are useful in various techniques for image processing and analysis. In particular, the book covers applications in object representation and shape analysis. With many figures (some in color) and end-of-chapter exercises, this book provides an in-depth, unified account of digital metrics, the characterization of digital curves and straight lines, and their uses in shape analysis. It gives you insight on the latest two- and three-dimensional image processing applications.

As more images and videos are becoming available in compressed formats, researchers have begun designing algorithms for different image operations directly in their domains of representation, leading to faster computation and lower buffer requirements. Image and Video Processing in the Compressed Domain presents the fundamentals, properties, and applications of a variety of image transforms used in image and video compression. It illustrates the development of algorithms for processing images and videos in the compressed domain. Developing concepts from first principles, the book introduces popular image and video compression algorithms, in particular JPEG, JPEG2000, MPEG-2, MPEG-4, and H.264 standards. It also explores compressed domain analysis and performance metrics for comparing algorithms. The author then elucidates the definitions and properties of the discrete Fourier transform (DFT), discrete cosine transform (DCT), integer cosine transform (ICT), and discrete wavelet transform (DWT). In the subsequent chapters, the author discusses core operations, such as image filtering, color enhancement, image resizing, and transcoding of images and videos, that are used in various image and video analysis approaches. He also focuses on other facets of compressed domain analysis, including video editing operations, video indexing, and image and video steganography and watermarking. With MATLAB® codes available as a download from the CRC Press website, this book takes you through the steps involved in processing and analyzing compressed videos and images. It covers the algorithms, standards, and techniques used for coding images and videos in compressed formats.

Exploring theories and applications developed during the last 30 years, Digital Geometry in Image Processing presents a mathematical treatment of the properties of digital metric spaces and their relevance in analyzing shapes in two and three dimensions. Unlike similar books, this one connects the two areas of image processing and digital geometry, highlighting important results of digital geometry that are currently used in image analysis and processing. The book discusses different digital geometries in multi-dimensional integral coordinate spaces. It also describes interesting properties of the geometries, including metric and topological properties, shapes of circles and spheres, proximity to Euclidean norms, and number theoretic representations of geometric objects such as straight lines and circles. The authors—all active researchers in image processing and digital geometry—demonstrate how these concepts and properties are useful in various techniques for image processing and analysis. In particular, the book covers applications in object representation and shape analysis. With many figures (some in color) and end-of-chapter exercises, this book provides an in-depth, unified account of digital metrics, the characterization of digital curves and straight lines, and their uses in shape analysis. It gives you insight on the latest two- and three-dimensional image processing applications.

As more images and videos are becoming available in compressed formats, researchers have begun designing algorithms for different image operations directly in their domains of representation, leading to faster computation and lower buffer requirements. Image and Video Processing in the Compressed Domain presents the fundamentals, properties, and applications of a variety of image transforms used in image and video compression. It illustrates the development of algorithms for processing images and videos in the compressed domain. Developing concepts from first principles, the book introduces popular image and video compression algorithms, in particular JPEG, JPEG2000, MPEG-2, MPEG-4, and H.264 standards. It also explores compressed domain analysis and performance metrics for comparing algorithms. The author then elucidates the definitions and properties of the discrete Fourier transform (DFT), discrete cosine transform (DCT), integer cosine transform (ICT), and discrete wavelet transform (DWT). In the subsequent chapters, the author discusses core operations, such as image filtering, color enhancement, image resizing, and transcoding of images and videos, that are used in various image and video analysis approaches. He also focuses on other facets of compressed domain analysis, including video editing operations, video indexing, and image and video steganography and watermarking. With MATLAB® codes on an accompanying CD-ROM, this book takes you through the steps involved in processing and analyzing compressed videos and images. It covers the algorithms, standards, and techniques used for coding images and videos in compressed formats.