Byeung-woo Jeon

Blocking artifacts reduction in image coding based on minimum block boundary discontinuity

This paper proposes a novel blocking artifacts reduction method which is based on the notion that the blocking artifacts are present in images due to heavy accuracy loss of transform coefficients in the quantization process. We define the block boundary discontinuity measure as the sum of the squared differences of pixel values along the block boundary. The proposed method makes correction of the selected transform coefficients so that the resultant image has minimum block boundary discontinuity. It does not specify a transform domain where the correction should take place, therefore an appropriate transform domain can be selected at users discretion. In the experiments, the scheme is applied to DCT- based compressed images to show its performance.

Irregular triangular mesh representation based on adaptive control point removal

Several new approaches are being investigated in conjunction with the low bit rate coding, such as MPEG-4, to overcome the limitation imposed by block-based image compression. One solution is to use warping prediction (or spatial transformation) based on a set of control points where one of the most important issues is how to adequately place the control points not destroying salient features such as edges and corners. In this paper, we propose a new image representation scheme based on irregular triangular mesh structure in which, considering the salient features, a considerably reduced number of control points are adaptively selected out of initial uniformly distributed control points. A new criterion based on local representation error is defined to be used in successive control point removal exploiting global image features, thus providing better image representation. Computer simulation has shown that the proposed scheme gives significantly improved image representation performance compared with the conventional scheme based on regular meshes in both objective and subjective qualities.

Application of dynamic Huffman coding to image sequence compression

In many image sequence compression applications, Huffman coding is used to reduce statistical redundancy in quantized transform coefficients. The Huffman codeword table is often pre-defined to reduce coding delay and table transmission overhead. Local symbol statistics, however, may be much different from the global one manifested in the pre-defined table. In this paper, we propose a dynamic Huffman coding method which can adaptively modify the given codeword and symbol association according to the local statistics. Over a certain set of blocks, local symbol statistics is observed and used to re-associate the symbols to the codewords in such a way that shorter codewords are assigned to more frequency symbols. This modified code table is used to code the next set of blocks. A parameter is set up so that the relative degree of sensitivity of the local statistics to the global one can be controlled. By performing the same modification to the code table using the decoded symbols, it is possible to keep up with the code table changes in receiving side. The code table modification information need not be transmitted to the receiver. Therefore, there is no extra transmission overhead in employing this method.