K. Dezhgosha, M. M. Jamali, and S. C. Kwatra. A VLSI architecture for realtime image coding using a vector quantization based algorithm. IEEE Trans. on Signal Processing, pages 181--189, January 1992.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....It is currently under investigation for image compression, where it outperforms the current standard by Joint Picture Experts Group (JPEG) There is also a strong interest in dedicated hardware for VQ. Several integrated circuits have been implemented specifically for VQ [DG86, FCS90, KYJ93, DJK92, DB87] Problem: Vector Quantization Vector quantization finds in a set of codevectors the vector most similar to the source vector, a sequence of digitized signal samples. Applications other than compression also require such a dedicated engine: VQ has been used in segmenting images [GBJM79] ....

....of the VQ computation have been investigated in the literature. The intent of these investigations has been primarily to decrease computation time. Few have also considered the storage aspect. Dezhgosha and et al. have investigated compressing codebook using conventional compression techniques [DJK92] Our research differs in that it examines arithmetic to decrease the complexity of VQ and improve its implementation. We investigate both storage and computation aspect. Moreover, since the gains are in arithmetic of classification, our approach can be applied in variety of algorithms using ....

[Article contains additional citation context not shown here]

K. Dezhgosha, M. M. Jamali, and S. C. Kwatra. A VLSI architecture for realtime image coding using a vector quantization based algorithm. IEEE Trans. on Signal Processing, pages 181--189, January 1992.

....complexity of VQ encoders and the extremely fast speeds demanded by real time video applications. While much of the research effort directed at image compression via VQ has not been directly applicable to real time hardware coding architectures, some recent proposals have been put forward ([5], 6] 7] and [8] Unfortunately, the actual performance of VQ of real video signals in real time has not been sufficiently demonstrated. The DVQ hardware presented here represents a real time demonstration of the merits of VQ. The organization of this report is as follows. Part I describes the ....

....were designed for speech; however, real time video encoding requires significantly faster processing. Rather than attempt full search VQ at these rates, several proposed architectures for real time video VQ are based on the suboptimal techniques discussed above. For example, Dezhgosha et al. [5] propose an architecture based on mean residual VQ and Ramamoorthy et al. 22] propose using multi stage VQ. Recent advances in VLSI technology have made full search VQ at video rates possible. For example, Panchanthan and Goldberg [6] propose an architecture based on an exact match ....

[Article contains additional citation context not shown here]

K. Dezhgosha, M. M. Jamali, and S. C. Kwatra, "A VLSI Architecture for Real-Time Image Coding Using a Vector Quantization Based Algorithm," IEEE Transactions on Signal Processing, vol. 40, pp. 181--189, January 1992.

....complexity of VQ encoders and the extremely fast speeds demanded by realtime video applications. While much of the research effort directed at image compression via VQ has not been directly applicable to real time hardware coding architectures, some recent proposals have been put forward ([2], 3] 4] and [5] Unfortunately, the actual performance of VQ of real video signals in real time has not been sufficiently demonstrated. The work presented here represents a real time demonstration of the merits of VQ. In this paper, we begin with a review of VQ and previously proposed ....

....were designed for speech; however, real time video encoding requires significantly faster processing. Rather than attempt full search VQ at these rates, several proposed architectures for real time video VQ are based on the suboptimal techniques discussed above. For example, Dezhgosha et al. [2] propose an architecture based on mean residual VQ and Ramamoorthy et al. 12] propose using multi stage VQ. Recent advances in VLSI technology have made fullsearch VQ at video rates possible. For example, Panchanthan and Goldberg [3] propose an architecture based on an exact match CAM. More ....

[Article contains additional citation context not shown here]

K. Dezhgosha, M. M. Jamali, and S. C. Kwatra, "A VLSI Architecture for Real-Time Image Coding Using a Vector Quantization Based Algorithm," IEEE Transactions on Signal Processing, vol. 40, pp. 181-- 189, January 1992.

....several proposed architectures for real time video VQ are based on suboptimal techniques. These suboptimal alternatives typically restrict the codeword search to a subset of the codebook or split the quantization into separate steps that each use smaller codebooks. For example, Dezhgosha et al. [5] propose an architecture based on mean residual VQ and Ramamoorthy et al. 6] propose using multi stage VQ. Recent advances in VLSI technology have made fullsearch VQ at video rates possible. For example, Panchanthan and Goldberg [7] propose an architecture with an exact match content addressable ....

....[7] propose an architecture with an exact match content addressable memory (CAM) More recently, analog VQ encoding chips have been fabricated by Fang et al. 8] and Tuttle et al. 9] However, none of the above have actually demonstrated performance of VQ on real time video. A number of papers [5, 6, 7] have presented proposals for hardware architectures, but few have actually fabricated their designs. The analog designs of [8] and [9] suffer from limited precision and conclusive operational behavior for realtime video has not been proven for either. Artificial Neural Networks and VQ The ....

K. Dezhgosha, M. M. Jamali, and S. C. Kwatra, "A VLSI Architecture for Real-Time Image Coding Using a Vector Quantization Based Algorithm," IEEE Transactions on Signal Processing, vol. 40, pp. 181--189, January 1992.

....complexity of VQ encoders and the extremely fast speeds demanded by real time video applications. While much of the research effort directed at image compression via VQ has not been directly applicable to realtime hardware coding architectures, some recent proposals have been put forward [2, 3, 4, 5]. Unfortunately, the actual performance of VQ of real video signals in real time has not been sufficiently demonstrated. The work presented here represents a real time demonstration of the merits of VQ. In this paper, we begin with a review of previously proposed hardware VQ architectures. Next, ....

....several proposed architectures for real time video VQ are based on suboptimal techniques. These suboptimal alternatives typically restrict the codeword search to a subset of the codebook or split the quantization into separate steps that each use smaller codebooks. For example, Dezhgosha et al. [2] propose an architecture based on mean residual VQ and Ramamoorthy et al. 6] propose using multi stage VQ. Recent advances in VLSI technology have made full search VQ at video rates possible. For example, Panchanthan and Goldberg [3] propose an architecture based on an exact match ....

[Article contains additional citation context not shown here]

K. Dezhgosha, M. M. Jamali, and S. C. Kwatra, "A VLSI Architecture for Real-Time Image Coding Using a Vector Quantization Based Algorithm," IEEE Transactions on Signal Processing, vol. 40, pp. 181--189, January 1992.

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K. Dezhgosha, M. M. Jamali, S. C. Kwatra, "A VLSI Architecture for Real-Time Image Coding Using a Vector Quantization Based Algorithm", IEEE Transactions on Signal Processing, Vol. 40, No. 1, pp. 181-189, Jan. 1992.

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K. Dezhgosha, M. Jamali and S. Kwatra: "A vlsi architecture for real-time image coding using a vector quantization based algorithm", IEEE Trans. on Signal Processing, 40, 1, pp. 181--189 (1992).

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K. Dezhgosha, M. M. Jamali, and S. C. Kwatra, "A VLSI Architecture for Real-Time Image Coding Using a Vector Quantization Based Algorithm," IEEE Transactions on Signal Processing, vol. 40, pp. 181--189, January 1992.

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