Based on the theory of block projection onto convex sets (BPOCS), a novel de-blocking algorithm is proposed. A new smoothness constraint set (SCS) is used to remove the unnecessary high frequencies. In addition, an adaptive quantization constraint set (AQCS) is employed to suppress error in the smoothing process. The proposed size and position of new SCS are different from traditional ones. Extensive experimental results are provided to demonstrate that the proposed method can achieve better image quality with fewer iterations.

A novel image resizing algorithm is proposed. In our method, three steps are included in the downsampling: the first-round downsampling, the interim upsampling and the second-round downsampling. The downsampling operation unit size is selected between one single 1616 block size and four 88 block sizes during the first-round downsampling processing. To distinguish the selected downsampling operation unit size, the interim upsampling and the second-round downsampling is required. The DCT coefficients of the interim upsampling image indicate the selected downsampling unit size. The DCT coefficients are converted by some way like lifting step and simultaneously downsampled in the second round. The information about selected operator unit size is contained in the final downsampling image. Experimental results demonstrate the proposed method achieves better result than the relevant existing method.