On Visually Lossless JPEG Image Compression

This paper presents an investigation into the visually lossless JPEG compression which provides maximum compression ratio applied before the resulting compressed image appears distorted. The research was conducted using two publicly available databases with the results of just noticeable difference tests. It has been shown that using visually lossless compression can save memory and communication resources by 80% compared to conventional JPEG compression approach with a fixed quality factor. Compared to JPEG lossless compression, this saves memory resources by about eight times. Also, it is shown that the mean gradient magnitude of the original uncompressed image can be used to predict the JPEG visually lossless compression ratio. The last part of the research provides comments on visually lossless quality prediction using a simple prediction approach based on only one feature of the original image with a comparison with the results of a deep learning approach.