• Korean Journal of Remote Sensing
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• v.7 no.1
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• pp.69-86
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• 1991

An unsupervised region based image segmentation algorithm implemented with a pyramid structure has been developed. Rather than depending on thraditional local splitting and merging of regions with a similarity test of region statistics, the algorithm identifies the homogenous and boundary regions at each level of pyramid, then the global parameters of esch class are estimated and updated with values of the homogenous regions represented at the level of the pyramid using the mixture distribution estimation. The image is then classified through the pyramid structure. Classification results obtained for both simulated and SPOT imagery are presented.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.7
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• pp.566-577
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• 1991

In this paper, the method of image segmentation based on a pyramid of reduced resolution versions of the input input image is persented. In a pyramid structure, two regions (a given pixel and its mother pixels) are compared by the proposed inverse-mother-son variance ratio (IMSVR) method for the detection of an optinal object pixel and are determined whether they are similar enough to be viewed as one region or disparate to be viewed as ditinct regions By the proposed method, an l`timal object pixel has been setectedat some level, it is necessary to retrieve its boundary precisely. Moving down the pyramid to levels of higher resolution is requires. In this paper, the top-sown pyramid traversing algorithm for an image segmentation using a pyrmid structure is presented. Using the computer simulation, the results by the proposed statistical method and object traversing method are investigated for the binary image and the real image at the results of computer simulation, the proposed method of image segmentation based on a pyramid structure seem to have useful properties and deserve consideration as a possible alternative to existing methods of omage segmentation. The computation for the proposed method is required 0 (log n), for an TEX>$n{\times}n$ input image.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.3
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• pp.664-668
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• 2010

This paper presents a System-On-a-chip (SoC) for embedded image processing and pattern recognition applications that need Gaussian Pyramid structure. The system is fully implemented into Field-Programmable Gate Array (FPGA) based on the prototyping platform. The SoC consists of embedded processor core and a hardware accelerator for Gaussian Pyramid construction. The performance of the implementation is benchmarked against software implementations on different platforms.

• Journal of Korea Multimedia Society
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• v.19 no.7
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• pp.1154-1158
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• 2016

This paper presents a System-On-a-chip for embedded image processing applications that need Gaussian Pyramid structure. The system is fully implemented into Field-Programmable Gate Array (FPGA) based on the prototyping platform. The SoC consists of embedded processor core and a hardware accelerator for Gaussian Pyramid construction. The performance of the implementation is benchmarked against software implementations on different platforms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.12
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• pp.3033-3045
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• 1996

In this paper, we propse an object-oriented coding method in low bit-rate channels using pyramid structure and residual image compensation. In the motion estimation step, global motion is estimated using a set of multiresolution images constructed in a pyramid structure. We split an input image into two regions based on the gradient value. Regions with larte motions obtain observation points at low resolution level to guarantee robustness to noise and to satisfy a motion constraint equation whereas regions with local motions such as eye, and lips get observation points at the original resolution level. Local motion variations and intesity variations of an image reconstructed by the golbal motion are compensated additionally by using the previous residual image component. Finally, the model failure (MF) region is compensated by the pyramid mapping of the previous displaced frame difference (DFD). Computer simulation results show that the proposed method gives better performance that the convnetional one in terms of the peak signal to noise ratio (PSNR), compression ratio (CR), and computational complexity.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.8
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• pp.1227-1237
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• 1989

In this paper, we propose a lossless progressive image transmission scheme using hierarchical pyramid structure and classified vector quantizer in DCT domain. By adopting DCT to the hierarchical pyramid signals, we can reduce the spatial redundance. Moreover, the DCT coefficients can be encoded efficiently by using classified vector quantizer in DCT domain. The classifier is simply based on the variance of a subblock. Also, the mirror set of training set of images can improve the robustness of codebooks. Progressive image transmission can be achieved through following processes: from top to bottom level of planes in a pyramid, and from high to low AC variance class in a plane. Some simulation results with real images show that the proposed coding scheme yields a good performance at below 0.3 bpp and an excellent result at 0.409 bpp. The proposed coding scheme is well suited for lossless progressive image transmission as well as image data compression.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1988.10a
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• pp.257-261
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• 1988

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.10
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• pp.1561-1570
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• 1989

In this paper, we propose an image coding scheme which combines the Laplacian pyramid structure and a hierarchical finite state classified vector quantizer in the DCT domain, namely FSDCT-CTQ. First, an optimal bit allocation problem for fixed rates DCT-CVQ on the Laplacian pyramid structure is described. In an asymptotic case, with an optimal bit allocation, a coding gain over scalar quantization of each Laplacian plane is derived. Second, it is experimentallhy shown that the Laplacian pyramid structure provides a considerable codng gain in the sense of total MMSE (minimum mean squared error). Finally, we propose an FS-DCT-CVQ which exploits the hierarchicla correlation between the Laplacian planes. Simulation results on real images show that the proposed coding scheme can reconstruct an image with 30.33 dB at 0.192 bpp, 32.45 dB at 0.385 bpp, respectively.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.283-294
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• 2022

The feature map used in the network for deep learning generally has larger data than the image and a higher compression rate than the image compression rate is required to transmit the feature map. This paper proposes a method for transmitting a pyramid feature map with high compression rate, which is used in a network with an FPN structure that has robustness to object size in deep learning-based image processing. In order to efficiently compress the pyramid feature map, this paper proposes a structure that predicts a pyramid feature map of a level that is not transmitted with pyramid feature map of some levels that transmitted through the proposed prediction network to efficiently compress the pyramid feature map and restores compression damage through the proposed reconstruction network. Suggested mAP, the performance of object detection for the COCO data set 2017 Train images of the proposed method, showed a performance improvement of 31.25% in BD-rate compared to the result of compressing the feature map through VTM12.0 in the rate-precision graph, and compared to the method of performing compression through PCA and DeepCABAC, the BD-rate improved by 57.79%.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.5
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• pp.90-102
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• 1993

In this paper, we propose a prgressive image transmission technique using hierarchical pyramid data structure which is constructed based on the projection data of an image. To construct hierarchical Gaussian pyramids, we first divide an image into 4$\times$4 subblocks and generate the projection data of each block along the horizontal, vertical, diagonal, and antidiagonal directions. Among images reconstructed by backprojecting the projection data along a single direction, the one giving the minimum distortion is selected. The Gaussian pyramid is recursively generated by the proposed algorithm and the proposed Gaussian images are shown to preserve edge information well. Also, based on the projection concept a new transmission scheme of the lowest Laplacian plane is presented. Computer simulation shows that the quantitative performance of the proposed pyramid coding technique using projection concept is similar to those of the conventional methods with transmission rate reduced by 0.1 ~ 0.2 bpp and its subjective performance is shown to be better due to the edge preserving property of a projection operation.