Advanced image coding and its comparison with various still image codecs

Abstract— JPEG is a popular DCT-based still image compression standard, which has played an important role in image storage and transmission since its development. Advanced Image Coding (AIC) is a still image compression system which combines the intra frame block prediction from H.264 with a JPEG-based discrete cosine transform followed by context adaptive binary arithmetic coding (CABAC). It performs much better than JPEG and has the best performance at low bit rates. In this paper, we propose a modified AIC (M-AIC) by replacing the CABAC in AIC with a Huffman coder and an adaptive arithmetic coder. The results are compared with other image compression techniques like JPEG, JPEG2000, JPEG-LS and JPEG-XR on various sets of test images. This paper considers JPEG only using baseline method and all the codecs are considered in lossy compression. Simulation results are evaluated in terms of bit-rate, qualityPSNR and structural similarity index (SSIM). The simulation results based on PSNR demonstrate that M-AIC has optimal performance for images of all resolutions, whereas JPEG 2000 has a good performance for high resolution images and a performance several dB lower than M-AIC for low resolution images. AIC has the best results for low resolution images whereas its performance lies in between JPEG and JPEG2000 for higher resolution images. The performance of still image codecs like M-AIC, JPEG-LS and JPEG-XR does not depend on the image resolution, which makes them suitable for wide varieties of applications. SSIM simulation results illustrate that M-AIC, JPEG2000 and JPEG-XR have similar performance and are better than any other codecs. JPEG follows the above trend with little SSIM scale difference. JPEG-LS follows the other codecs and excels only at higher bit rates.