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COMPARISON OF VISULALLY LOSSLESS COMPRESSION OF DENTAL IMAGES BY DIFFERENT CODERS BASED ON HAARPSI METRIC

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The object of the study is the process of visually lossless compression of dental images by means of five coders using HaarPSI metrics and its distortion invisibility threshold. The subject of the study is the method for selection of parameters that control compression to provide invisibility of distortions with further comparison of performance characteristics for the considered coders. The goal of the study is to analyze compression ratio range for image fragments of different complexity and to give recommendations concerning coders to be used and their parameters setting. Methods used: numerical simulation, verification for a set of test images. Results obtained: 1) the compression ratios vary in rather wide limits depending on image complexity and noise characteristics; 2) the coders AGU-M and BPG produce the best compression ratios for the same visual quality compared to other considered coders; 3) there is high correlation of compression ratios of the considered coders. Conclusions: 1) it is possible to provide rather large compression ratios without losing diagnostically valuable information; 2) adapting the compression to image complexity allows significant increasing of compression ratios for simple structure images. 
Title: COMPARISON OF VISULALLY LOSSLESS COMPRESSION OF DENTAL IMAGES BY DIFFERENT CODERS BASED ON HAARPSI METRIC
Description:
The object of the study is the process of visually lossless compression of dental images by means of five coders using HaarPSI metrics and its distortion invisibility threshold.
The subject of the study is the method for selection of parameters that control compression to provide invisibility of distortions with further comparison of performance characteristics for the considered coders.
The goal of the study is to analyze compression ratio range for image fragments of different complexity and to give recommendations concerning coders to be used and their parameters setting.
Methods used: numerical simulation, verification for a set of test images.
Results obtained: 1) the compression ratios vary in rather wide limits depending on image complexity and noise characteristics; 2) the coders AGU-M and BPG produce the best compression ratios for the same visual quality compared to other considered coders; 3) there is high correlation of compression ratios of the considered coders.
Conclusions: 1) it is possible to provide rather large compression ratios without losing diagnostically valuable information; 2) adapting the compression to image complexity allows significant increasing of compression ratios for simple structure images.
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