Performance Improvement of Vector Quantization by Using Threshold
Vector quantization (VQ) is an elementary technique for image compression. However, the complexity of searching the nearest codeword in a codebook is time-consuming. In this work, we improve the performance of VQ by adopting the concept of THRESHOLD. Our concept utilizes the positional information to represent the geometric relation within codewords. With the new concept, the lookup procedure only need to calculate Euclidean distance for codewords which are within the threshold, thus sifts candidate codewords easily. Our scheme is simple and suitable for hardware implementation. Moreover, the scheme is a plug-in which can cooperate with existing schemes to further fasten search speed. The effectiveness of the proposed scheme is further demonstrated through experiments. In the experimental results, the proposed scheme can reduce 64% computation with only an extra storage of 512 bytes.
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