• Title/Summary/Keyword: Quantization levels

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Reversible Data Hiding in Block Truncation Coding Compressed Images Using Quantization Level Swapping and Shifting

  • Hong, Wien;Zheng, Shuozhen;Chen, Tung-Shou;Huang, Chien-Che
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.6
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    • pp.2817-2834
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    • 2016
  • The existing reversible data hiding methods for block truncation coding (BTC) compressed images often utilize difference expansion or histogram shifting technique for data embedment. Although these methods effectively embed data into the compressed codes, the embedding operations may swap the numerical order of the higher and lower quantization levels. Since the numerical order of these two quantization levels can be exploited to carry additional data without destroying the quality of decoded image, the existing methods cannot take the advantages of this property to embed data more efficiently. In this paper, we embed data by shifting the higher and lower quantization levels in opposite direction. Because the embedment does not change numerical order of quantization levels, we exploit this property to carry additional data without further reducing the image quality. The proposed method performs no-distortion embedding if the payload is small, and performs reversible data embedding for large payload. The experimental results show that the proposed method offers better embedding performance over prior works in terms of payload and image quality.

A Performance Improvement of GLCM Based on Nonuniform Quantization Method (비균일 양자화 기법에 기반을 둔 GLCM의 성능개선)

  • Cho, Yong-Hyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.2
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    • pp.133-138
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    • 2015
  • This paper presents a performance improvement of gray level co-occurrence matrix(GLCM) based on the nonuniform quantization, which is generally used to analyze the texture of images. The nonuniform quantization is given by Lloyd algorithm of recursive technique by minimizing the mean square error. The nonlinear intensity levels by performing nonuniformly the quantization of image have been used to decrease the dimension of GLCM, that is applied to reduce the computation loads as a results of generating the GLCM and calculating the texture parameters by using GLCM. The proposed method has been applied to 30 images of $120{\times}120$ pixels with 256-gray level for analyzing the texture by calculating the 6 parameters, such as angular second moment, contrast, variance, entropy, correlation, inverse difference moment. The experimental results show that the proposed method has a superior computation time and memory to the conventional 256-level GLCM method without performing the quantization. Especially, 16-gray level by using the nonuniform quantization has the superior performance for analyzing textures to another levels of 48, 32, 12, and 8 levels.

Implement of Fuzzy Inference Hardware for Servo Control Using $\alpha$ -level Set Decomposition ($\alpha$-레벨집합 분해에 의한 서보제어용 퍼지추론 하드웨어의 구현)

  • Hong Soon-ill;Lee Yo-seob;Choi Jae-yong
    • Proceedings of the KIPE Conference
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    • 2001.07a
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    • pp.662-665
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    • 2001
  • As the fuzzy control is applied to servo system the hardware implementation of the fuzzy information systems requires the high speed operations, short real time control and the small size systems. The aims of this study is to develop hardware of the fuzzy information systems to be apply to servo system. In this paper, we propose a calculation method of approximate reasoning for fuzzy control based on $\alpha$-level set decomposition of fuzzy sets by quantize $\alpha$-cuts. This method can be easily implemented with analog hardware. The influence of quantization levels of $\alpha$-cuts on output from fuzzy inference engine is investigated. It is concluded that 4 quantization levels give sufficient result for fuzzy control performance of do servo system. It examined useful with experiment for dc servo system.

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Improved Channel Level Difference Quantization for Spatial Audio Coding

  • Kim, Kwang-Ki;Beack, Seung-Kwon;Seo, Jeong-Il;Jang, Dae-Young;Hahn, Min-Soo
    • ETRI Journal
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    • v.29 no.1
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    • pp.99-102
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    • 2007
  • The channel level difference (CLD) is a main parameter in the reference model 0 (RM0) for MPEG Surround. Nevertheless, the CLD quantization method in the RM0 has problems such as the lack of theoretical background and inappropriate quantization levels. In this letter, a new CLD quantization method is proposed based on the virtual source location information which has strength in the quantization process. From experimental results, it is confirmed that the proposed scheme greatly reduces the quantization distortions measured in dB and degrees without any additional complexity.

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A Fuzzy Resoning for Servo System by $\alpha$-Level Set Decomposition and Hardware Implementation ($\alpha$-레벨집합 분해에 의한 서보시스템용 퍼지추론과 하드웨어)

  • 안영주
    • Proceedings of the KIPE Conference
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    • 2000.07a
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    • pp.38-40
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    • 2000
  • In this paper we propose a calculation method for fuzzy control based on quantized $\alpha$-cut decomposition of fuzzy sets. This method is easy to be implemented in analog hardware. The effect of quantization levels on defuzzified fuzzy inference results is investigated. A few quantization levels are sufficient for fuzzy control. The hardware implementation of this calculation method and the defuzzification by gravity center method by PWM are also presented.

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A DCT-based hierarcical finite state vector quantization for image coding (영상 부호화를 위한 이산 여현변환 기반의 계층적 유한 상태 벡터 양자화 기법)

  • 남일우;김응성;이근영
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.1
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    • pp.88-95
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    • 1998
  • In this paper, we introduce a new DCT based hierarchical finite state vector quantization. Our proposed scheme uses difference of DCT coefficients to find a representative vector, and classifies image blocks into different hierarchical levels depending on their structural characteristics, and uses different coding rates and different number os state codebooks at each hierarchical levels. As a result, we obtained reconstructed images having satisfiable quality objectively.

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A Calculation Method for fuzzy Control by $\alpha$-cut Decomposition and Its Hardware Implementation (\alpha$-레벨집합 분해에 의한 퍼지제어 추론계산법과 하드웨어에 관한 연구)

  • 홍순일;이요섭;장용민
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2001.06a
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    • pp.133-136
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    • 2001
  • In this paper, we propose a calculation method for fuzzy control based on quantized $\alpha$ -cut decomposition of fuzzy sets. This method is easy to be implemented in analog hardware. The effect of quantization levels on defuzzified fuzzy inference result is investigated. A few quantization levels are sufficient for fuzzy control. The hardware implementation of this calculation method and the defuzzificaion by gravity center method by PWM are also presented.

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Enhancement Method of Depth Accuracy in DIBR-Based Multiview Image Generation (다시점 영상 생성을 위한 DIBR 기반의 깊이 정확도 향상 방법)

  • Kim, Minyoung;Cho, Yongjoo;Park, Kyoung Shin
    • KIPS Transactions on Computer and Communication Systems
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    • v.5 no.9
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    • pp.237-246
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    • 2016
  • DIBR (Depth Image Based Rendering) is a multimedia technology that generates the virtual multi-view images using a color image and a depth image, and it is used for creating glasses-less 3-dimensional display contents. This research describes the effect of depth accuracy about the objective quality of DIBR-based multi-view images. It first evaluated the minimum depth quantization bit that enables the minimum distortion so that people cannot recognize the quality degradation. It then presented the comparative analysis of non-uniform domain-division quantization versus regular linear quantization to find out how effectively express the accuracy of the depth information in same quantization levels according to scene properties.

Reduction Method of Added Information Generated by Increasing the Number of Quantizer Reconstruction Levels (양자화 복원 레벨 개수 증대로 발생되는 부가정보 감소방법)

  • Wu, Ya-Lin;Kwon, Soon-Kak;Kwon, Oh-Jun
    • Journal of Korea Multimedia Society
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    • v.13 no.8
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    • pp.1154-1162
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    • 2010
  • Because it is easy to implement the scalar quantizer, it is used in various video coding systems. Although the scalar quantizer with a large quantization stepsize can reduce the amount of data, it has disadvantage that the reconstructed picture quality is poor. In this paper, we propose an efficient method which improves the coding performance by maintaining original quantization stepsize and increasing the number of quantization reconstruction levels. Simultaneously, for the purpose of solving the problem of transmitting the added symbol informations which is used to indicate the region of quantizer reconstruction level as the number of quantizer reconstruction level is increased, we also suggest the method to reduce the added informations. Therefore, for the intra-coded picture of H.264 video coding system, we generate the huffman codes for the symbol informations of quantization reconstruction regions by 4${\times}$4(horizontal 4 pixels, vertical pixels) block unit. Furthermore, for the inter-coded picture, we also generate the huffman codes for the symbol informations of quantization reconstruction regions by 8${\times}$8 blocks and 4${\times}$4 blocks within a macroblock. Adopting this method of reducing the added information by increasing the number of quantization reconstruction region, It is shown that the coding performance can be improved at the same bitrate.

Terrain Classification Using Three-Dimensional Co-occurrence Features (3차원 Co-occurrence 특징을 이용한 지형분류)

  • Jin Mun-Gwang;Woo Dong-Min;Lee Kyu-Won
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.52 no.1
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    • pp.45-50
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    • 2003
  • Texture analysis has been efficiently utilized in the area of terrain classification. In this application features have been obtained in the 2D image domain. This paper suggests 3D co-occurrence texture features by extending the concept of co-occurrence to 3D world. The suggested 3D features are described using co-occurrence histogram of digital elevations at two contiguous position as co-occurrence matrix. The practical construction of co-occurrence matrix limits the number of levels of digital elevation. If the digital elevation is quantized into the number of levels over the whole DEM(Digital Elevation Map), the distinctive features can not be obtained. To resolve the quantization problem, we employ local quantization technique which preserves the variation of elevations. Experiments has been carried out to verify the proposed 3D co-occurrence features, and the addition of the suggested features significantly improves the classification accuracy.