Publication

A comparative study of color image compression standards using perceptually driven quality metrics

Abstract

The task of comparing the performance of different codecs is strictly related to the research in the field of objective quality metrics. Even if several objective quality metrics have been proposed in literature, the lack of standardization in the field of objective quality assessment and the lack of extensive and reliable comparisons of the performance of the different state-of-the-art metrics often make the results obtained using objective metrics not very reliable. In this paper we aim at comparing the performance of three of the existing alternatives for compression of digital pictures, i.e. JPEG, JPEG 2000, and JPEG XR compression, by using different objective Full Reference metrics and considering also perceptual quality metrics which take into account the color information of the data under analysis.

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Related concepts (20)
Lossy compression
In information technology, lossy compression or irreversible compression is the class of data compression methods that uses inexact approximations and partial data discarding to represent the content. These techniques are used to reduce data size for storing, handling, and transmitting content. The different versions of the photo of the cat on this page show how higher degrees of approximation create coarser images as more details are removed. This is opposed to lossless data compression (reversible data compression) which does not degrade the data.
Image compression
Image compression is a type of data compression applied to s, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data. Image compression may be lossy or lossless. Lossless compression is preferred for archival purposes and often for medical imaging, technical drawings, clip art, or comics.
Data compression
In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information.
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