Surapong Lertrattanapanich

Superresolution with second generation wavelets

Over the last 3 years or so, first-generation wavelets have been used to realize superresolution from a captured sequence of low-resolution (LR) degraded frames. Here, it is pointed out that second-generation wavelets (SGWs) are inherently more suited for image superresolution. From preliminary results that exploit subpixel displacements between LR frames to attain superresolution, it is concluded that SGWs show promise and potential to be extremely fast, efficient and versatile for superresolution.

Low line memory visually lossless compression for color images using non-uniform quantizers

The paper proposes a novel method to compress color images with imperceptible quality loss. The algorithm explores the difference in error perceptibility of human visual system (HVS) for various areas. It is done by implementing different non-uniform quantizers for flat, detail and random blocks of pixels. These blocks are classified based on principle component analysis (PCA) and prediction error. For hardware implementation purpose, the algorithm is designed to use very low line memory. Simulation results show that the proposed compression is visually lossless in all categories of tested images with high compression ratio.

Real time video stabilization with reduced temporal mismatch and low frame buffer

This paper proposes a real time video stabilization method which only requires a low number of buffered frames. The effect of temporal mismatch between the original and deshaked frames to the black border artifacts is also considered. This mismatch effect is then removed by delaying the motion compensation with a suitable number of frames. To minimize the number of buffered frames, the deshaking filter is designed to have smallest filter delay. Simulation shows that the proposed stabilization filter effectively removes the shaky motions and has reduced black border artifacts.

Visually lossless compression for color images with low line memory requirement using non-uniform quantizers

The paper proposes a novel method to compress color images with imperceptible quality loss. The algorithm explores the difference in error perceptibility of human visual system for various areas. It is done by implementing different non-uniform quantizers for flat, detail and random blocks of pixels. These blocks are classified based on principle component analysis (PCA) and prediction error. For hardware implementation purpose, the algorithm was designed to use very low line memory. Simulation results show that the proposed compression is visually lossless in all categories of tested images with high compression ratio.

Automatic video deshearing for skew sequences capturedby rolling shutter cameras

A novel automatic video deshearing is proposed to reduce the skew artifacts (jelly artifacts) in sequences captured by CMOS censor cameras. The paper first considers the principles of skew artifacts in rolling shutter cameras. Then a deshearing algorithm with high accuracy is discussed with automatic skew artifact detection. A video completion step is also implemented to reconstruct unavailable pixels in the new grid of the desheared frame. Simulation results show that the proposed method effectively reduces the skew artifacts for different sequences captured by rolling shutter cameras.