Jun Seok Song

Block-based wavelet transform coding of mammograms with region-adaptive quantization

To achieve both high compression ratio and information preserving, it is an efficient way to combine segmentation and lossy compression scheme. Microcalcification in mammogram is one of the most significant sign of early stage of breast cancer. Therefore in coding, detection and segmentation of microcalcification enable us to preserve it well by allocating more bits to it than to other regions. Segmentation of microcalcification is performed both in spatial domain and in wavelet transform domain. Peak error controllable quantization step, which is off-line designed, is suitable for medical image compression. For region-adaptive quantization, block- based wavelet transform coding is adopted and different peak- error-constrained quantizers are applied to blocks according to the segmentation result. In view of preservation of microcalcification, the proposed coding scheme shows better performance than JPEG.

Multistage temporal motion compensation for motion vector coding

Motion vector field is generally encoded by using an intraframe differential coding, that is, the well known DPCM approach. An interframe differential coding might be an alternative when the motion vector field is not spatially smooth enough. In this paper, we propose a multistage interframe differential coding approach. In addition to the temporal dependencies between the motion vector fields, temporal dependencies between residual vector fields of consecutive stages are also exploited in this approach. An accumulated average for generating the compensation vector field is also proposed in this paper. Experimental results have shown that the proposed approach is more suitable for real applications where various characteristics of motion fields might exist.

Sequential vector quantization of directionally decomposed DCT coefficients

A new transform domain vector quantizer has been introduced for efficient image coding which employs directional decomposition and sequential vector quantization of DCT coefficients (DCT-SVQ): the DCT coefficients are decomposed into 16 slightly-overlapping subvectors for a subvector to convey key information about one directional image, and then the decomposed subvectors are vector quantized sequentially. The scheme has the capability of the rate control with no need for changing the codebooks and reveals good performance over a wide range of code rates. This paper addresses the improvement of that scheme by (1) adjusting the quantization step size of the DC quantizer as well as the AC quantizers according to the target distortion of the reconstructed image and (2) introducing the activity of an image block to the decision of the appropriate stopping condition of the sequential vector quantizer for that block.<<ETX>>

Sequential vector quantization of perceptually windowed DCT coefficients

In order to provide a high quality of the reconstructed images with a reduced transmission bit rate, taking into account both statistical redundancy and perceptual characteristics of the DCT coefficients, we apply perceptual windowing and sequential vector quantization to encoding of the coefficients: first, the coefficients are decomposed into 16 slightly overlapping subvectors so as that each subvector has reasonable dimension and conveys key information about one directional image, and then the decomposed subvectors are quantized in a sequential manner. The proposed scheme is good at encoding images with a wide range of transmission bit rates which can be easily controlled by adjusting only the stopping criterion of the sequential vector quantizer.

Region-adaptive JPEG encoding scheme for medical images

This paper presents a region adaptive encoding scheme with JPEG decoder compatibility. This scheme adequately changes the Lagrange multiplier in R-D cost function for each block according to the segmentation information so that the important region for diagnosis can be coded with less distortion. The results show that the proposed scheme not only outperforms original JPEG but also outperforms R-D optimal thresholding JPEG in important regions with respect to image fidelity.

Lossless progressive compression of medical images

This paper presents a lossless image compression method, which provides progressive transmission property and scalability. The proposed method enables the codec to have an asymmetric structure by employing a fast adaptive subband decomposition and the optimization of the quantization parameter during arithmetic coding. This method provides a higher compression ratio than JPEG lossless mode.

Wavelet compression of medical image using tree-structured vector quantization and high-order entropy coding

A tree-structured vector quantization system employing conditional arithmetic coding is introduced to encode wavelet coefficients of medical image. The proposed scheme efficiently reduces bit rate by exploiting inter- and intra- band correlation and effectively approximates the embedded scheme by utilizing sequential bit allocation results of the nested quantizers. The proposed scheme provides good bitrate-PSNR performance and subjective reconstruction quality with lower encoding complexity than the wavelet full-search vector quantization systems.

Memory-constrained high-order entropy coding by Huffman table sharing and memory allocation

For memory constrained high-order entropy coding, (i) the number of Huffman tables and (ii) the size of each Huffman table have to be appropriately reduced. Recently, we developed a Huffman table sharing and a memory allocation methods, each of which efficiently reduces either (i) or (ii) to meet the given memory constraint while keeping the increase in average bitrate as small as possible. However, given a memory constraint, the Huffman table sharing and the memory allocation methods have to be employed at the same time to achieve the better result. This paper presents several efficient schemes for combining the two methods along with simulation results.