Vector-centered CAM architecture for image coding using vector quantization

S. Panchanathan, M. Goldberg

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


In this paper, a vector-centered CAM architecture for image coding using vector quantization is presented. In vector quantization(VQ), a set of representative vectors (codebook) is generated from a training set of vectors. The input vectors to be coded are quantized to the closest codeword of the codebook and the corresponding index(label) of the codeword is transmitted. Thus, VQ essentially involves a search operation to obtain the best match. Traditionally, the search mechanism is implemented sequentially, where each vector is compared with the codewords one at a time. For K input vectors of dimension L, and a codebook of size N, the search complexity is O(KLN) which is compute intensive making real-time implementation of VQ algorithm difficult. A content-addressable memory (CAM) based architecture (where the data is accessed simultaneously and in parallel on the basis of its content) which exploits parallelism in the directions of L and K resulting in real-time implementation of VQ has been reported6. Here, the CAM cell is essentially pixel-centered and hence K*L cells have to be organized in L parallel modules, K cells per module, which implies a large hardware complexity. Furthermore, the results of the search operation in the individual modules have to be combined which involves a high communication overhead. In this paper, we propose a vector-centered CAM cell which essentially stores the entire vector (Vij) in a cyclic stack. The individual pixels in the vector are then circulated into the search portion of the cell. The result of the search operation are stored in a response register which is also organized within the cell. The proposed design has the advantages of reduced hardware complexity, low communication overhead and modularity which make possible VLSI implementation of the architecture. An analysis of the savings in hardware complexity, and communication overhead is also presented in this paper.

Original languageEnglish (US)
Pages (from-to)1084-1094
Number of pages11
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - Nov 1 1989
Externally publishedYes

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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