Quantization (image processing)

About: Quantization (image processing) is a research topic. Over the lifetime, 7977 publications have been published within this topic receiving 126632 citations.

Efficient rate control for multi-resolution video encoding

Abstract: The invention provides a multi-resolution video encoding system which improves the computational efficiency associated with encoding a video sequence in two or more different resolutions. An illustrative embodiment includes a first encoder for encoding the sequence at a first resolution, and a second encoder for encoding the sequence at a second resolution higher than the first resolution. Information obtained from encoding the sequence at the first resolution is used to provide rate control for the sequence at the second resolution. This information may include, for example, a relationship between a quantization parameter selected for an image at the first resolution and a resultant output bitrate generated by encoding the image using the selected quantization parameter. The invention can be used with a variety of video encoding standards, including H.261, H.263, Motion-JPEG, MPEG-1 and MPEG-2.

Image vector quantization algorithm via honey bee mating optimization

Abstract: The vector quantization (VQ) was a powerful technique in the applications of digital image compression. The traditionally widely used method such as the Linde-Buzo-Gray (LBG) algorithm always generated local optimal codebook. Recently, particle swarm optimization (PSO) is adapted to obtain the near-global optimal codebook of vector quantization. An alternative method, called the quantum particle swarm optimization (QPSO) had been developed to improve the results of original PSO algorithm. In this paper, we applied a new swarm algorithm, honey bee mating optimization, to construct the codebook of vector quantization. The results were compared with the other three methods that are LBG, PSO-LBG and QPSO-LBG algorithms. Experimental results showed that the proposed HBMO-LBG algorithm is more reliable and the reconstructed images get higher quality than those generated from the other three methods.

Image coding apparatus

Abstract: An image coding apparatus that makes possible the parallelization of intra prediction, and outputs coded data that can be decoded by an image decoding apparatus compliant with the H264 standard The image coding apparatus performs orthogonal transformation, quantization, inverse quantization, inverse orthogonal transformation, and intra prediction on all blocks obtained when a single macroblock is divided into plural blocks, and includes: a predicted block control unit that causes all of the blocks to be intra predicted using at least one of the intra prediction modes specified in the H264 standard on at least some of the blocks, in an order different from the raster scan order specified in the H264 standard; and an sorting buffer that outputs, in the raster scan order, all the blocks intra predicted under the control of the predicted block control unit

Image sharpening in the JPEG domain

Abstract: We present a new technique for sharpening compressed images in the discrete-cosine-transform domain. For images compressed using the JPEG standard, image sharpening is achieved by suitably scaling each element of the encoding quantization table to enhance the high-frequency characteristics of the image. The modified version of the encoding table is then transmitted in lieu of the original. Experimental results with scanned images show improved text and image quality with no additional computation cost and without affecting compressibility.