Quaternion-Sparse Image Processing: Advances in Multispectral Processing

Brings together the technologies, research, and managerial applications of quaternion-sparse based complex algebra in image processing. The book covers the entire range of complicated tasks performed on color images, including denoising, reconstruction, classification, hallucination, feature extraction, dimension reduction, and regularization. It provides easy understanding and smooth adaptability of basic and advanced concepts for graduate students, researchers, doctors, academics, and practitioners.

Uncovers the innovative features of complex algebra, specifically the quaternion-sparse concept in image processing and how it can help in improving the computational efficiency of image processing

Deals with the most common quaternion convolution neural network, quaternion wavelet, and sparse representation-based techniques in multispectral image processing

Focuses on how evolution in algebraic concepts, i.e., quaternion and sparse, help in improving accuracy and efficiency of various color image restoration, reconstruction, and recognition

Illustrates how important features are extracted and complete information is stored in extracted features to help and process tasks in an easy and computationally efficient way