Quality Control for the BPG Lossy Compression of Three-Channel Remote Sensing Images

This paper deals with providing the desired quality in the Better Portable Graphics (BPG)-based lossy compression of color and three-channel remote sensing (RS) images. Quality is described by the Mean Deviation Similarity Index (MDSI), which is proven to be one of the best metrics for characterizin...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2022-04, Vol.14 (8), p.1824
Main Authors: Li, Fangfang, Lukin, Vladimir, Ieremeiev, Oleg, Okarma, Krzysztof
Format: Article
Language:English
Subjects:
Accuracy
BPG coder
Classification
Coders
Compression
Compression ratio
Distortion
Image compression
Image quality
image quality assessment
lossy image compression
Mean
Parameters
Quality control
Remote sensing
remote sensing images
Variance
Visibility
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Summary:This paper deals with providing the desired quality in the Better Portable Graphics (BPG)-based lossy compression of color and three-channel remote sensing (RS) images. Quality is described by the Mean Deviation Similarity Index (MDSI), which is proven to be one of the best metrics for characterizing compressed image quality due to its high conventional and rank-order correlation with the Mean Opinion Score (MOS) values. The MDSI properties are studied and three main areas of interest are determined. It is shown that quite different quality and compression ratios (CR) can be observed for the same values of the quality parameter Q that controls compression, depending on the compressed image complexity. To provide the desired quality, a modified two-step procedure is proposed and tested. It has a preliminary stage carried out offline (in advance). At this stage, an average rate-distortion curve (MDSI on Q) is obtained and it is available until the moment when a given image has to be compressed. Then, in the first step, an image is compressed using the starting Q determined from the average rate-distortion curve for the desired MDSI. After this, the image is decompressed and the produced MDSI is calculated. In the second step, if necessary, the parameter Q is corrected using the average rate-distortion curve, and the image is compressed with the corrected Q. Such a procedure allows a decrease in the MDSI variance by around one order after two steps compared to variance after the first step. This is important for the MDSI of approximately 0.2–0.25 corresponding to the distortion invisibility threshold. The BPG performance comparison to some other coders is performed and examples of its application to real-life RS images are presented.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs14081824