Author Description

Measurement of image quality is necessary for many image processing applications. In general image quality assessment (IQA) is based on the differences or similarity between a degraded image and the original, unmodified image.There are two ways to measure image quality by subjective or objective assessment. Subjective evaluations are expensive and time-consuming. So it is impossible to implement them into automatic real-life systems. So there is need of objective evaluations which are automatic and mathematical defined algorithms. In this book various types of objective measure in respect to image processing have studied. Main purpose is to highlight the application of these measures in the various fields of digital image processing like, image enhancement, image compression, image denoising. Moreover, grouping of quality measures have done depending on image characteristics like pixel, edge, spatial-frequency domain which are based on statistical attributes. Ultimately image quality measures are the best tool for analysis of any image processing algorithms.