Publisher's Synopsis
In today's world, countless number of images are collected using various image acquisition devices. The course of actions taken to enhance the acquired image quality, to extract meaningful information from the acquired image, and to represent these information in a compact fashion is known as image processing. Digital image processing is the use of computer algorithms to perform image processing on digital images. A digital image is a numeric representation of a two-dimensional image. Depending on whether the image resolution is fixed, it may be of vector or raster type. The term "digital image" usually refers to raster images, also called bitmap images. With the fast computers and signal processors available since 2000, digital image processing has become the most common and cheapest form of image processing. Chapter 1 introduces approaches to estimate depth information for 3D video services. In order to reduce computational complexity and to enhance accuracy of stereo matching, a hierarchical structure of selective cost aggregation is presented. Chapter 2 introduces a multiple camera system which is composed of the multiple color and time-of-flight depth cameras. The proposed method covers the scene capturing using the camera system, post-processing of the captured images, and multi-view depth generation. Chapter 3 presents a novel framework for facilitating the development of vision-based human gesture/action control applications. The proposed approach takes 3D perceptual shape features and the prior knowledge of the human body to build 4D qualitative gesture representation for recognition tasks. Chapter 4 concerned with a system in which most of the motions in the scenes are conservative or near-conservative in a certain temporal interval with multiple image sequences. Chapter 5 illustrates applications on image databases, especially those which are dedicated to plant organelle research, and present their potential as comprehensive resources for image-based computational analyses. Chapter 6 presents the deconvolution of linear combinations of Gaussian convolution using an imhomogeneous Fredholm integral equation of second kind and the Liouville-Neumann series. Applications are given for image processing and photon/proton dosimetry. Chapter 7 discusses how to model illumination variations with a quadric function, and relight the skin pixels with a simple operation. The methodology is illustrated with three typical color imaging applications involving human skin: face detection, hand gesture recognition, and pigmented skin lesion segmentation. Chapter 8 presents a new feature-preserving denoising method for images with textures. The proposed approach combines regularized anisotropic diffusion and recent harmonic analysis techniques into a nonlinear partial differential equation sensitive to edge and texture detection. Chapter 9 aims at explaining how to apply perceptual criteria in order to define a perceptual forward and inverse quantizer and in addition to present its application to the Hi-SET coder. Chapter 10 proposed an object-based hybrid image coding algorithm, which works more efficiency than the SPIHT coding method. Chapter 11 highlights how classical nonlinear filtering methods, widely used for signal and image denoising, can be successfully applied for the efficient solution of Compressed Sensing reconstruction problems. Chapter 12 proposes a real time algorithms for numerical realization of integral transformation of the Fourier. Chapter 13 explores basic concepts and implementation techniques underlying the Digital Television that made it possible to capture, process, store and broadcast digitized moving pictures. Chapter 14 presents a technique to perform joint entropy coding and encryption for AVS video codec using AES encryption technique in CFB mode.
