JPEG and BPG visually lossless image compression via KonJND-1k database.

Introduction/purpose: This paper presents the results of the research on visually lossless image compression which is of particular interest because it achieves a high degree of compression, while the visual quality of the image is not impaired, i.e., end users are very satisfied with the image quality. The analysis was carried out using the publicly available large-scale picture-wise KonJND-1k database which contains the results of subjective tests on JPEG and BPG compressed images. Methods: Thanks to the availability of images from the KonJND-1k database, the dependence of objective assessments of image quality on parameters that control the degree of compression of source signals (quality factor for JPEG and quantization parameter for BPG) is analyzed. The results of the visually lossless subjective tests are used for a deep analysis of the boundary and typical values of the parameters that control these two types of compression, as well as for the analysis of the corresponding values of the objective quality scores. Furthermore, reliable features for predicting the boundary between visually lossless and visually lossy compression have been identified. For that purpose, the degree of agreement between the predictions and the ground truth values of the peak signal-to-noise ratio (PSNR) and image representation in bits per pixel (bpp) is used. The visually lossless compression ratio is used to compare JPEG and BPG techniques. Results: It is shown that the boundary between visually lossless and visually lossy image compression is found in a wide range of PSNR values (about 20 dB for JPEG and 15 dB for BPG). The corresponding JPEG image compression quality factor values at this threshold also range widely from 31 to 79, with concentration between 40 and 45. For the BPG encoder, the values of the quantization parameter are grouped around 30, and the boundary values are 25 and 34. Furthermore, it is shown that this boundary can be reliably determined based on simple features derived from the original uncompressed image. Gradient-based features known as spatial frequency and spatial information proved to be the best predictors. The degree of agreement between the predictions obtained from these features with the ground truth values of PSNR and bpp in both types of compression is greater than 85%. A comparative analysis has showed that, using BPG compression, it is possible, on the average, to achieve a twice larger compression ratio of visually lossless compression than for JPEG (80 versus 40). Conclusion: Although a high degree of agreement is achieved between the predictions and the ground truth values of PSNR and bpp of the boundary between visually lossless and visually lossy compression, there is a need for the development of new prediction approaches, especially with the BPG technique, which through the compression ratio proved to be superior to the JPEG technique. The existing databases used for the analysis of visually lossless compression contain color images from the visible part of the electromagnetic spectrum. Considering the increasing use of images from the infrared part of the spectrum, there is a need to conduct similar tests in this spectral range. [ABSTRACT FROM AUTHOR]