• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.1
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• pp.81-92
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• 1999

In this paper, we propose a new image segmentation algorithm which can be use din object-based image coding applications such as MPGA-4. Since the conventional objet segmentation methods based on mathematical morphology tend to yield oversegmented results, they normally need a postprocess which merges small regions to obtain a larger one. To solve this oversegmentation problem, in this paper, we prosed a block-based segmentation algorithm that can identify large texture regions in the image. Also, by applying the watershed algorithm to the image blocks between the homogeneous regions, we can obtain the exact pixel-based contour. Experimental results show that the proposed algorithm yields larger segments, particularly in the textural area, and reduces the computational complexities.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.124-132
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• 2014

In this paper, we present a novel backlit region detection and contrast enhancement method using fuzzy C-means clustering and adaptively partitioned block based contrast stretching. The proposed method separates an image into both dark backlit and bright background regions using adaptively partitioned blocks based on the optimal threshold value computed by fuzzy logic. The detected block-wise backlit region is refined using the guided filter for removing block artifacts. Contrast stretching algorithm is then applied to adaptively enhance the detected backlit region. Experimental results show that the proposed method can successfully detect the backlit region without a complicated segmentation algorithm and enhance the object information in the backlit region.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.5
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• pp.187-195
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• 2005

A new segmentation-based image coding method which no needs transmission of contour data is proposed. The shape information acts as bottleneck in the segmentation-based video coding because it has much portion of transmission data. The proposed method segments a previous decoded frame, instead of a current frame. As a result, there is no need for transmission of contour information to a decoder. Therefore, the saved bits can be assigned to encode other information such as error signals. As shown in experiment results, if data rate is very highly increased due to abrupt motion under very low bit rate coding having limited transmission bits, PSNR of conventional block-based method go down about 20dB, while the proposed method shows a good reconstruction quality without rapid PSNR drop.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.4 s.304
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• pp.119-126
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• 2005

We propose a new content-based image retrieval using a representative color histogram and directional pattern histogram that is adaptive to the classification characteristics of the image blocks. In the proposed method the color and pattern feature vectors are extracted according to the characteristics o: the block classification after dividing the image into blocks with a fixed size. First, the divided blocks are classified as either luminance or color blocks depending on the saturation of the block. Thereafter, the color feature vectors are extracted by calculating histograms of the block average luminance co-occurrence for the luminance block and the block average colors for the color blocks. In addition, block directional pattern feature vectors are extracted by calculating histograms after performing the directional gradient classification of the luminance. Experimental results show that the proposed method can outperform the conventional methods as regards the precision and the size of the feature vector dimension.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.15-17
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• 2018

VVC(Versatile Video Coding)는 입력된 영상을 CTU(Coding Tree Unit) 단위로 분할하여 코딩하며, 이를 다시 QTBTT(Quadtree plus binary tree and triple tree)로 분할하고, TU(Transform Unit)도 이와 같은 단위로 분할된다. 따라서 TU의 크기는 $4{\times}4$, $4{\times}8$, $4{\times}16$, $4{\times}32$, $8{\times}4$, $16{\times}4$, $32{\times}4$, $8{\times}8$, $8{\times}16$, $8{\times}32$, $16{\times}8$, $32{\times}8$, $16{\times}16$, $16{\times}32$, $32{\times}16$, $32{\times}32$, $64{\times}64$의 17가지 종류가 있다. 기존의 VVC 참조 Software인 VTM에서는 디블록킹필터와 SAO(Sample Adaptive Offset)로 이루어진 인루프필터를 이용하여 에러를 복원하는데, 본 논문은 TU 크기에 따라서 원본블록과 복원블록의 차이(에러)가 통계적으로 다름을 이용하여 서로 다른 CNN(Convolution Neural Network)을 구축하고 에러를 복원하는 방법으로 VTM의 인루프 필터를 대체한다. 복원영상의 에러를 감소시키기 위하여 TU 블록크기에 따라 DenseNet의 Dense Block기반 CNN을 구성하고, Hyper Parameter와 복잡도의 감소를 위해 네트워크 간에 일부 가중치를 공유하는 모양의 Network를 구성하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2003.11a
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• pp.47-50
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• 2003

본 논문에서는 동영상을 효율적으로 부호화하기 위한 새로운 다중해상도 움직임 보상 방법과 잉여 양자화 방법을 제안한다. 본 논문에서 제안하는 동영상 부호화기는 다단계 이산웨이브렛 분해 움직임 예측 및 움직임 보상 블록 Tree 의 구성 및 블록 분할. 적응적 산술 부호화기로 구성된다 제안된 동영상 부호화기는 단순하면서도 낮은 연산량을 필요로 하며, 임베디드 특성과 SNR 계위 부호화 특성과 같은 좋은 기능을 제공한다. 또한 기존에 제안되었던 이산웨이브렛변환을 이용하는 동영상 부호화 방법과 비교하여 우수한 성능을 제공한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.105-111
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• 2009

In this paper, we propose a locally adaptive image restoration method based on nonlinear extrapolation in frequency domain. In general, the conventional method causes ringing artifacts on the object boundary. To solve this problem, we introduce an improved restoration method which considers textures of an image block. In the proposed method, a blurred image is divided into several blocks, and each block is classified into three groups; simple, one edge, and complex blocks according to the contained texture. Depending on the classification result, adaptive nonlinear extrapolation is applied to each block in a blurred image. Experimental results show that the proposed algorithm can achieve higher quality image in both subjective and objective views as compared with the conventional method.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.327-336
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• 2002

Texture analysis is an important technique in many image understanding areas, such as perception of surface, object, shape and depth. But the previous works are intend to the issue of only texture segment, that is not capable of acquiring recognition information. No unsupervised method is basased on the recognition of texture in image. we propose a novel approach for efficient texture image analysis that uses unsupervised learning schemes for the texture recognition. The self-organization neural network for multiple texture image identification is based on block-based clustering and merging. The texture features used are the angle and magnitude in orientation-field that might be different from the sample textures. In order to show the performance of the proposed system, After we have attempted to build a various texture images. The final segmentation is achieved by using efficient edge detection algorithm applying to block-based dilation. The experimental results show that the performance of the system Is very successful.

• Journal of the Korea Society of Computer and Information
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• v.19 no.6
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• pp.1-10
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• 2014

In this paper, we propose a real-time video playback scheme for the N-Screen service based on Windows Azure. This scheme creates several playback blocks based on the performance of each node by non-uniform splitting of the original video. To reduce transcoding-time, it allocates the playback blocks to a corresponding node by transcoding the playback blocks. Through the simulation, we show that it is more effective to use real-time video playback for the N-screen service than the previous method. The proposed scheme splits an AVI format 300MB source video with non-uniform playback blocks. It allocates the playback blocks to the heterogeneous node of Windows Azure, the commercial cloud system and measures of transcoding-time by transcoding non-uniform playback blocks to mp4 and Flv format. As a result, the proposed scheme improves the performance of the N-screen service based on Windows Azure compared to the previous uniform split strategy.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.1
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• pp.15-24
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• 2008

This paper proposes a scheme of global image contrast enhancement using local contrast improvement. Methods of global image contrast enhancement redistribute the image gray level distribution using histogram equalization without considering image properties, and cause the result image to include image pixels with excessive brightness. On the other hand, methods of the block-based local image contrast enhancement have blocking artifacts and a problem of eliminating important image features during an image process to reduce them. In order to solve these problems, the proposed method executes the block-based histogram equalization on temporary images that an input image is divided into various fixed-size blocks. And then it performs the global contrast enhancement by applying the global histogram equalization functions to the original input image. Since the proposed method selects the best histogram equalization function from temporary images that are improved by the block-based local image contrast enhancement, it has the advantages of both the local and global image contrast enhancement approaches.