• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.31-38
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• 1994

This paper proposed signal decomposition and multiresolution representation through wavelet transform using wavelet orthonormal basis. And it suggested most appropriate filter for scaling function in multiresoltion representation and compared two compression method, arithmetic coding and Huffman coding. Results are as follows 1. Daub18 coefficient is most appropriate in computing time, energy compaction, image quality. 2. In case of image browsing that should be small in size and good for recognition, it is reasonable to decompose to 3 scale using pyramidal algorithm. 3. For the case of progressive transmittion where requires most grateful image reconstruction from least number of sampls or reconstruction at any target rate, I embedded the data in order of significance after scaling to 5 step. 4. Medical images such as information loss is fatal have to be compressed by lossless method. As a result from compressing 5 scaled data through arithmetic coding and Huffman coding, I obtained that arithmetic coding is better than huffman coding in processing time and compression ratio. And in case of arithmetic coding I could compress to 38% to original image data.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06a
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• pp.83-88
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• 1999

In this paper, a novel gray-scale lossless image coder combining context-based minimum mean squared error (MMSE) prediction and entropy coding is proposed. To obtain context of prediction, this paper first defines directional difference according to sharpness of edge and gradients of localities of image data. Classification of 4 directional differences forms“geometry context”model which characterizes two-dimensional general image behaviors such as directional edge region, smooth region or texture. Based on this context model, adaptive DPCM prediction coefficients are calculated in MMSE sense and the prediction is performed. The MMSE method on context-by-context basis is more in accord with minimum entropy condition, which is one of the major objectives of the predictive coding. In entropy coding stage, context modeling method also gives useful performance. To reduce the statistical redundancy of the residual image, many contexts are preset to take full advantage of conditional probability in entropy coding and merged into small number of context in efficient way for complexity reduction. The proposed lossless coding scheme slightly outperforms the CALIC, which is the state-of-the-art, in compression ratio.

• Journal of Biomedical Engineering Research
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• v.10 no.3
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• pp.243-252
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• 1989

In this study, medical images, which are X-ray image and CT image, are compressed by the adam live coding technique. The medical images may be treated as special ones, because they are different from general images in many respects. The statistical characteristics that medical images only have in transform domain are analyzed, and then the improved quantization method is proposed for medical images. For chest X-ray image and CT head image, the better results are obtained by the improved adaptive coding technique.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1803-1806
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• 2002

This paper describes an effective technique for lossless inter-frame video coding sequences based on a JPEG2000 CODEC. This technique has diminished the compression rate for lossless video coding. In this proposed method, firstly a predicted image for an in- put image is generated by motion estimation(ME), and then a difference image between the input image and the predicted image is calculated, and finally the difference image becomes an input image to a JPEG2000 encoder for lossless coding. Simulation results show the effectiveness of this method.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.3
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• pp.559-566
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• 2012

In this paper, we propose a fast fractal image coding algorithm to shorten long time to take on fractal image encoding. For its performance evaluation, the algorithm compares with other traditional fractal coding methods. In the traditional fractal image coding methods, an original image is contracted by a factor in order to make the corresponding image to be compared with. Then, the whole area of the contracted image is searched in order to find the fixed point of contractive transformation of the original image corresponding to the contracted image. It needs a lot of searching time on encoding. However, the proposed algorithm considerably reduces encoding time by using scaling method and limited search area method. On comparison of the proposed algorithm with Jacquin's method, the proposed algorithm is dozens of times as fast as that of Jacquin's method on encoding time with a little degradation of the decoded image quality and a little increase of the compression rate. Therefore, it is found that the proposed algorithm largely improves the performance in the aspect of encoding time when compared with other fractal image coding methods.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.211-214
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• 2001

This paper presents an efficient fast motion estimation algorithm and image segmentation method for low bit-rate coding. First, with region split information, the algorithm splits the image having homogeneous and semantic regions like face and semantic regions in image. Then, in these regions, We find the motion vector using adaptive search window adjustment. Additionally, with this new segment based fast motion estimation, we reduce blocking artifacts by intensively coding our interesting region(face or arm) in input image. The simulation results show the improvement in coding performance and image quality.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.88-96
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• 1994

In this paper, we propose a subband pyramid image coding scheme that uses ECVQ (ntropy Constrained Vector Quantizer). In subband pyramid image coding, each subband can be encoded with a coder matched to the statistics of that particular subband, and available versions of the original image at different resolution are easily obtained. ECVQ, aiming at the minimization of the distortion for a fixed entropy of the quantizer output, is well combined with the subband pyramid image coding which yields high compression ratio and good image quality. The optimum bit allocation to each subbands corresponds to the points where the individual distortion rate curves are of particular slope, weighted to the number of samples in that subband, in designing ECVQ.

• Transactions of the Society of Information Storage Systems
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• v.5 no.1
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• pp.36-40
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• 2009

We describe the experimental realization of image system using wavefront coding in 3-Mega pixel mobile phone camera. We designed aspheric lens to extend the depth of field (DOF) using wavefront coding. In addition, through the aspheric lens and lens barrel manufacturing, we obtained a raw image from a camera module. In our method, the acquired images are restored in the spatial frequency domain using the proposed filter and the spatial frequency response (SFR) is calculated. The proposed filters are composed of image denoising filter using low band pass filter in frequency domain and restoration filter for image restoration. Finally, we achieve an enhanced image by super-resolution image processing. Visual examples are given to demonstrate the performance of the proposed filter.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.05
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• pp.131-134
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• 1995

A three dimensional fractal coding with a perceptually enhanced matching is proposed. Since most of medical images (e.g. computed tomography or magnetic resonance image) have three dimensional character, the searching region is extended to adjacent slices. For perceptually enhanced matching, a high frequency booster filter is used for prefiltering of the original image, and the least mean square error matching is applied to this edge enhanced image rather than the original image. From the simulation with the magnetic resonance images ($255{\times}255$, 8bits/pixel). the proposed algorithm provides excellent image quality with compression rations higher than 10. Compared to existing fractal coding the algorithm also provides better subjective image quality with higher compression ratio.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.6
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• pp.937-943
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• 1990

In this paper, a subband coding scheme using the human visual system(HVS) model for encoding monochrome images is proposed to produce perceptually higher quality images compared with the regular subband coding scheme. The proposed approach first transforms the intensity image to the density image by a point nonlinear transformation. A frequency band dexomposition of the density image is carried out by means of 2-D seaprable quadrature mirror filters, which split the density image spectrum into 16 equall rate subbands. Bits are allocated among the subbands to minimize the weighted mean squar error (WMSE) for differential pulse code modulation(DPCM) coding of the subbands. The weight for each subband is calculated from the modulation transfer function (MTF) of the HVS model at corresponding frequencies. The performances of the proposed approach are evaluated for 256 * 256 monochrome images at the bit rates of 0.5, 0.75 and 1.0 bita per pixel. Computer simulation results indicate that using the HVS model yields more pleasing reconstructed images than regular subband coding approach which does not use HVS model.