An Indicator Elimination Method for Side-match Vector Quantization
نویسندگان
چکیده
The vector quantization (VQ) concept is widely used in many applications. Side-match vector quantization (SMVQ) is a VQ-based image compression method that offers significantly improved performance of compression rate while maintaining the image quality of decompressed images. To eliminate distortion propagation, SMVQ requires one extra bit to serve as an indicator identifying which blocks are encoded by SMVQ or VQ, and to make sure all image blocks can be successfully reconstructed. To eliminate the indicators generated by SMVQ, a reversible data hiding method is adopted to conceal indicator into the compression code. From experimental results, the proposed method successfully conceals indicators into compression code with similar visual quality performance to SMVQ. In addition, experimental results confirm that the proposed method significantly improves the performance of compression rate.
منابع مشابه
Three-sided side match finite state vector quantization
Several effective low bit rate still image compression methods have been presented in these two years, such as SPHIT [9], Hybrid VQ [7], Wu and Chen method [10]. These methods exercise the analysis techniques (wavelet or subband) before distributing the bit rate to each piece of image, thus the tradeoff between bit rate and distortion can be resolved. In this paper, we try to propose a simple b...
متن کاملImages Coding Using Two-Pass Side-Match Finite-State Vector Quantization
Among the image coding techniques, vector quantization (VQ) has been considered to be an effective method for coding images at low bit rate. The side-match finite-state vector quantizer (SMVQ) exploits the correlations between neighboring blocks (vectors) to avoid large gray level transition across block boundaries. In this paper, an improved SMVQ technique named two-pass side-match finite-stat...
متن کاملA New Side-Match Finite-State Vector Quantization Using Neural Networks for Image Coding
The side-match finite-state vector quantization (SMVQ) schemes improve performance over the vector quantization by exploiting the neighboring vector correlations within the image. In this paper, we propose a neural network side-match finite-state vector quantization (NN-SMVQ) scheme that combines the techniques of neural network prediction and the SMVQ coding method. In our coding scheme, the m...
متن کاملOrthogonal Polynomials based Image coding scheme using Side-Match Finite-State Classified Vector Quantization and SVM
In the previous chapters, orthogonal polynomials based image coding techniques with scalar quantization and vector quantizations were presented. The main drawback of these techniques was the edge degradation in the reconstructed image. Edges constitute a significant portion of the information content of an image and their degradation is visually annoying. To overcome this problem, a new image c...
متن کاملA Survey on Joint Data-Hiding and Compression Techniques based on SMVQ and Improved Locally Adaptive Coding Method
Today Reversible data hiding is latest research area in the field of secret data hiding technique. Data hiding is a technique in which conceal secret data is hidden in some cover image like video, audio, movie, file, and image. Data hiding popularly used in medical and military application. This paper covers many hiding and compression techniques like vector quantization (VQ), side match vector...
متن کامل