• Journal of Broadcast Engineering
• /
• v.13 no.1
• /
• pp.109-118
• /
• 2008

In mapping a texture image into a 3D mesh model for photo-realistic graphic applications, the compression of texture image is as important as geometry of 3D mesh. Typically, the size of the (compressed) texture image of 3D model is comparable to that of the (compressed) 3D mesh geometry. Most 3D model compression techniques are to compress the 3D mesh geometry, rather than to compress the texture image. Well-known image compression standards (i.e., JPEG) have been extensively used for texture image compression. However, such techniques are not so efficient when it comes to compress an image with texture patches, since the patches are little correlated. In this paper, we proposed a preprocessing method to substantially improve the compression efficiency of texture compression. From the experimental results, the proposed method was shown to be efficient in compression with a bit-saving from 23% to 45%.

• The Journal of Natural Sciences
• /
• v.4
• /
• pp.191-220
• /
• 1991

A new texture segmentation-based image coding technique which performs segmentation based on roughness of textural regions and properties of the human visual system (HVS) is presented. This method solves the problems of a segmentation-based image coding technique with constant segments by proposing a methodology for segmenting an image texturally homogeneous regions with respect to the degree of roughness as perceived by the HVS. The fractal dimension is used to measure the roughness of the textural regions. The segmentation is accomplished by thresholding the fractal dimension so that textural regions are classified into three texture classes; perceived constant intensity, smooth texture, and rough texture. An image coding system with high compression and good image quality is achieved by developing an efficient coding technique for each segment boundary and each texture class. For the boundaries, a binary image representing all the boundaries is created. For regions belonging to perceived constant intensity, only the mean intensity values need to be transmitted. The smooth and rough texture regions are modeled first using polynomial functions, so only the coefficients characterizing the polynomial functions need to be transmitted. The bounda-ries, the means and the polynomial functions are then each encoded using an errorless coding scheme. Good quality reconstructed images are obtained with about 0.08 to 0.3 bit per pixel for three different types of imagery ; a head and shoulder image with little texture variation, a complex image with many edges, and a natural outdoor image with highly textured areas.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.10
• /
• pp.5063-5073
• /
• 2016

In this paper, an efficient texture compression method is proposed for fast rendering, which exploits the spatial correlation among blocks through intra-picture block matching. Texture mapping is widely used to enhance the visual quality of results in real-time rendering applications. For fast texture mapping, it is necessary to identify an effective trade-off between compression efficiency and computational complexity. The conventional compression methods utilized for image processing (e.g., JPEG) provide high compression efficiency while resulting in high complexity. Thus, low complexity methods, such as ETC1, are often used in real-time rendering applications. Although these methods can achieve low complexity, the compression efficiency is still lower than that of JPEG. To solve this problem, we propose a texture compression method by reducing the spatial redundancy between blocks in order to achieve the better compression performance than ETC1 while maintaining complexity that is lower than that of JPEG. Experimental results show that the proposed method achieves better compression efficiency than ETC1, and the decoding time is significantly reduced compared to JPEG while similar to ETC1.

• Proceedings of the IEEK Conference
• /
• 2005.11a
• /
• pp.963-966
• /
• 2005

Previous works related to texture coordinate coding of the three-dimensional(3-D) mesh models employed the same predictor as the geometry coder. However, discontinuities in the texture coordinates cause unreasonable prediction. Especially, discontinuities become more serious for the 3-D mesh model with a non-atlas texture image. In this paper, we propose a new coding scheme to remove discontinuities in the texture coordinates by reallocating texture segments according to a coding order. Experiment results show that the proposed coding scheme outperforms the MPEG-4 3DMC standard in terms of compression efficiency. The proposed scheme not only overcome the discontinuity problem by regenerating a texture image, but also improve coding efficiency of texture coordinate compression.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.24 no.5
• /
• pp.914-922
• /
• 1987

An image coding technique based on a segmentation, which utilizes a simplified description of regions composing an image, is investigated in this paper. The proposed coding technique consists of 3 stages: segmentation, contour coding. In this paper, emphasis was given to texture coding in order to improve a quality of an image. Split-and-merge method was employed for a segmentation. In the texture coding, a linear predictive coding(LPC), along with approximation technique based on a two-dimensional polynomial function was used to encode texture components. Depending on a size of region and a mean square error between an original and a reconstructed image, appropriate texture coding techniques were determined. A computer simulation on natural images indicates that an acceptable image quality at a compression ratio as high as 15-25 could be obtained. In comparison with a discrete cosine transform coding technique, which is the most typical coding technique in the first-generation coding, the proposed scheme leads to a better quality at compression ratio higher than 15-20.

• The Journal of Natural Sciences
• /
• v.5 no.2
• /
• pp.33-38
• /
• 1992

A new texture segmentation-based image coding technique which performs segmentation based on roughness of textural regions and properties of the human visual system (HVS) is presented for multime-dia teleconference. The segmentation is accomplished by thresholding the fractal dimension so that textural regions are classified into three texture classes; perceived constant intensity, smooth texture, and rough texture. An image coding system with high compression and good image quality is achieved by developing an efficient coding technique for each segment boundary and each texture class. We compare the coding efficiency of this technique with that of a well established technique (discrete cosine transform (DCT) image coding).

• Journal of the Institute of Electronics Engineers of Korea TE
• /
• v.39 no.3
• /
• pp.83-89
• /
• 2002

A new scheme for image compression based on texture expression in the wavelet transform domain is presented. After taking wavelet transform, using the fact that the high-pass filtered bands has a lower variance than that of the original, a texture expression for the homogeneous polygonal regions can be more efficiently performed in the wavelet transform domain. The estimated texture parameters are transmitted to the receiver and later used for reconstruction after storing in disk. In most cases, the proposed method has yields good results with respects to the compression ratio and reconstructed image quality when our system has compared to conventional SPIHT scheme. 

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.3 no.3
• /
• pp.597-605
• /
• 1999

In this paper, we propose a cardioangiography sequence image coding scheme which use a subtraction between initial image and current frame inserted contrast dye. Stable regions are obtained by the multithreshold and meaningful region is extracted by the images with stable region. The image with meaningful region is classified into contour and texture information. Contour information is coded by contour coding. And texture information is approximated by two-dimensional polynomial function and each coefficients is coded. Experimental results confirm that the sequence of cardioangiography are well reconstructed at the low bit rate (0.02∼0.04 bpp) and high compression ratio.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.2
• /
• pp.45-55
• /
• 1994

In this paper, a block based image approximation technique using the Self Affine System(SAS) from the fractal theory is suggested. Each block of an image is divided into 4 tiles and 4 affine mapping coefficients are found for each tile. To find the affine mapping cefficients that minimize the error between the affine transformed image block and the reconstructed image block, the matrix euation is solved by setting each partial differential coefficients to aero. And to ensure the convergence of coding block. 4 uniformly partitioned affine transformation is applied. Variable block size technique is employed in order to applynatural image reconstruction property of fractal image coding. Large blocks are used for encoding smooth backgrounds to yield high compression efficiency and texture and edge blocks are divided into smaller blocks to preserve the block detail. Affine mapping coefficinets are found for each block having 16$\times$16, 8$\times$8 or 4$\times$4 size. Each block is classified as shade, texture or edge. Average gray level is transmitted for shade bolcks, and coefficients are found for texture and edge blocks. Coefficients are quantized and only 16 bytes per block are transmitted. Using the proposed algorithm, the computational load increases linearly in proportion to image size. PSNR of 31.58dB is obtained as the result using 512$\times$512, 8 bits per pixel Lena image.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.26 no.6
• /
• pp.89-96
• /
• 1989

An improved method on texture coding, which is a part of the region growing based image coding, is presented in this paper. An image is segmented into stochastic regions which can be described as a stochastic random field, and non-stochastic ones in order to efficiently represent texture. In the texture coding and reconstruction, an autoregressive model is used for the stochastic regions, while a two-dimensional polynomial approximation is used for the non-stochastic ones. This proposed method leads to a better subjective quality, relatively higher compression ratio and shorter processing time for coding and reconstructing than the conventional method which uses only two-dimensional polynomial approximation.