Journal ArticleDOI
Improvement on singular value decomposition vector quantization
Reads0
Chats0
TLDR
A quantization scheme where the minimum-distortion reconstruction is always provided in the original image space is developed and presented and its design algorithm is presented.Abstract:
For high-efficiency image compression, previously, an SVD (singular value decomposition)-based coder was developed using vector quantization, called SVD-VQ. This paper proposes an improved quantization SVD-VQ scheme. For every input subblock, the SVD-VQ coder scalar-quantizes a singular value and vector-quantizes two singular vectors, separately. The SVD-VQ decoder reproduces a subblock as the product of these quantization outputs, but does not necessarily produce a reconstruction with the minimum distortion in an image space. This paper develops a quantization scheme where the minimum-distortion reconstruction is always provided in the original image space and presents its design algorithm. The improved SVD-VQ shows A/N performance improvement of 0.5 - 1.0 dB over the conventional SVD-VQ, and is similar in performance to the adaptive DCT (discrete cosine transform) coder.read more
Citations
More filters
Proceedings ArticleDOI
Hybrid KLT-SVD image compression
P. Waldemar,Tor A. Ramstad +1 more
TL;DR: This paper investigates a transform adaptation technique, applied to transform coding of images, as a way of exploiting the variation in local statistics within an image, using the relationship between the Karhunen-Loeve transform and singular value decomposition and their energy compaction properties.
Journal ArticleDOI
Review: A variation on SVD based image compression
TL;DR: A variation to the well studied SVD based image compression technique that can be viewed as a preprocessing step in which the input image is permuted as per a fixed, data independent permutation, after which it is fed to the standard SVD algorithm.
Journal ArticleDOI
Hierarchical image coding via cerebellar model arithmetic computers
TL;DR: The proposed method, unlike the conventional hierarchical coding methods, uses no filtering technique in both decimation and interpolation processes, and has the following advantages: it does not suffer from problems of blocking effect, allowing lossless progressive image transmission.
Proceedings ArticleDOI
A hybrid scheme for encryption and watermarking
TL;DR: This paper presents a hybrid image protection scheme to establish a relation between the data encryption key and the watermark, and discusses on the data hiding capacity, watermark transparency, and robustness to common attacks.
Adaptive coding of monochrome and color images
Wen-Hsiung Chen,C. Smith +1 more
TL;DR: An efficient adaptive encoding technique using a new implementation of the Fast Discrete Cosine Transform (FDCT) for bandwidth compression of monochrome and color images is described, demonstrating excellent performance in terms of mean square error and direct comparison of original and reconstructed images.
References
More filters
Journal ArticleDOI
An Algorithm for Vector Quantizer Design
Y. Linde,A. Buzo,Robert M. Gray +2 more
TL;DR: An efficient and intuitive algorithm is presented for the design of vector quantizers based either on a known probabilistic model or on a long training sequence of data.
Journal ArticleDOI
Singular value decomposition and least squares solutions
Gene H. Golub,C. Reinsch +1 more
TL;DR: The decomposition of A is called the singular value decomposition (SVD) and the diagonal elements of ∑ are the non-negative square roots of the eigenvalues of A T A; they are called singular values.
Journal Article
Vector quantization
TL;DR: During the past few years several design algorithms have been developed for a variety of vector quantizers and the performance of these codes has been studied for speech waveforms, speech linear predictive parameter vectors, images, and several simulated random processes.
Journal ArticleDOI
Quantizing for minimum distortion
TL;DR: This paper discusses the problem of the minimization of the distortion of a signal by a quantizer when the number of output levels of the quantizer is fixed and an algorithm is developed to simplify their numerical solution.
Journal ArticleDOI
Image data compression: A review
TL;DR: A large variety of algorithms for image data compression are considered, starting with simple techniques of sampling and pulse code modulation (PCM) and state of the art algorithms for two-dimensional data transmission are reviewed.
Related Papers (5)
Combined techniques of singular value decomposition and vector quantization for image coding
Jar-Ferr Yang,Chiou-Liang Lu +1 more