A requantization algorithm for the transcoding of JPEG images

Photos from digital camera are mostly lossy compressed in JPEG format, and almost all users do not save or cannot access the original image. Sometimes we need to reduce the size of this JPEG file for saving the disk space or for sending the image to the device with limited bandwidth and/or display size. Since the original image is not available, we need to recompress the already compressed photos. In the existing literature, it is revealed that the direct transcoding (decompressing the JPEG image and then compressing it again with a larger step size) generally results in lower quality images when compared to the one compressed from the original image with the same parameters. This discrepancy is due to the requantization error, and the existing algorithms for more efficient transcoding were focused on finding the requantization step sizes for reducing this error. In this paper, we propose an algorithm that manipulates the requantized DCT coefficients for enhancing the quality of transcoded image, regardless of the choice of requantization step sizes. For this purpose, we first locate the DCT coefficients which have the possibility of causing large requantization errors. But, since the exact requantization error cannot be computed without the original image, we define the error as the discontinuity of pixels around the block boundaries, between the given JPEG image and the targeting one. Then, for the possible variants of these coefficients, the errors are computed and the best combination of coefficients is found. Experimental results show that more coefficients are correctly quantized than the conventional direct requantization, and thus the PSNR as well as the subjective quality is much improved.