Comparison Of Image Quality Metrics

Generally quality metrics are used to measure the quality of improvement in the images after they are processed and compared with the original and other different alternatives methods. Measurement of image quality is very crucial to many image processing applications. Compression is one of the applications where it is required to monitor the quality of decompressed / decoded image. JPEG compression is the lossy compression which is most prevalent technique for image codecs. But it suffers from blocking artifacts Here in this paper Various objective evaluation algorithms for measuring image quality like MSE, PSNR, SSIM and PSNR-B are simulated and compared w.r.t. JPEG compression application. Different deblocking filters are used to reduce blocking artifacts and deblocked images are compared through various quality metrics. As the degree of blocking depends on the quantization step, the quality metrics are also simulated and compared by varying the quantization step size. We discussed a new concept called ‘Modified PSNR-B’ which is under review process that gives even better results compared to the existing PSNR-B which includes the blocking effect factor (BEF). Keywords--Blocking artifacts, Deblocked images, Image quality, MSE, PSNR, SSIM, PSNR-B and Quantization