Estimating the compression quality of an image by analysing blocking artefacts

Abstract: Determining the compression quality of an image is important for photo forensics and image enhancement algorithms. Unfortunately, there are a number of issues involved in determining the compression quality of an image from its metadata or quantization tables. A compression quality estimation algorithm based on visual inspection of detected compression artefacts is presented. This method detects and extracts feature samples around compression block corners. These feature samples are then pre-filtered to enhance the discontinuities produced by compression artefacts. The feature samples are then classified using a constricted Neural Network. The local quality estimations are then combined using robust statistics to estimate the maximum likelihood compression quality. This method was shown to accurately estimate the compression quality of an image without prior knowledge of the original uncompressed image