JPEG-XR-GCP: Promoting JPEG-XR Compression by Gradient-Based Coefficient Prediction

JPEG-XR is a still-image compression standard with high compression ratio and low computation cost. It supports lossy and lossless coding for still images. To further improve the compression performance of JPEG-XR in both lossy and lossless modes, in this paper, we propose an improved JPEGXR by using gradient-based coefficient prediction (JPEG-XRGCP). The proposed JPEG-XR-GCP predicts the coefficients based on the estimating of local gradients, and predicts the value of coefficients adaptively by using its neighboring and secondorder neighboring coefficients in gradients. The experimental evaluations demonstrate that our proposed coding scheme has a better compression performance in both lossy and lossless modes compared with the original JPEG-XR.