Quantization (image processing)

About: Quantization (image processing) is a research topic. Over the lifetime, 7977 publications have been published within this topic receiving 126632 citations.

Optimization techniques for adaptive quantization of image and video under delay constraints

Abstract: Optimization techniques for adaptive quantization of image and video under delay constraints Antonio Ortega Traditionally, rate-distortion (R-D) theory has been concerned with providing bounds on the optimal performance for various classes of coding algorithms and sources. In this thesis we depart from that approach in two ways. First, our objective are operational R-D results, i.e. we study algorithms that can nd the optimal solution for a given coder con guration and known inputs, without relying on modeling either the encoder or the source. Second, we seek to explore explicitly other parameters that determine the achievable R-D performance, namely, the encoding delay and complexity, and the memory at the encoder. We compute the optimal solution even if it requires too much complexity, memory or delay to be considered in a practical setting. Optimal schemes serve as a benchmark and can also be the basis for heuristic methods which provide slightly suboptimal but more e cient performance. More speci cally we study the following topics: (i) Optimal bu er constrained quantization. We nd optimal solutions for the bu er control problem in a deterministic framework by assuming a long encoding delay. Our solution, based on dynamic programming, also leads us to short delay, lower complexity heuristics. (ii) Rate control and policing constraints for video transmission over ATM networks. We study the problem of optimizing the source quality as in (i), while taking into account network considerations. (iii) Optimization of dependent quantization environments. Optimal bit allocation results are presented for dependent quantization schemes (e.g. DPCM, predictive motion compensated video coding, MPEG). (iv) Rate-delay trade-o s in a multiresolution image database system. We study how the bit allocation in a multiresolution coding system can be chosen so as to minimize the end-to-end query delay in browsing through a set of images. (v) Adaptive quantization without side information. We propose a backward adaptive quantization algorithm where the input distribution is \learned" from past quantized samples. This allows adaptation to sources with unknown or time-varying input distribution. List of Abbreviations ATM Asynchronous Transfer Mode B Bidirectionally interpolated mode (in MPEG) CBR Constant Bit Rate DCT Discrete Cosine Transform DP Dynamic Programming DPCM Di erential Pulse Coded Modulation GAP Generalized Assignment Problem HDTV High De nition Television HVS Human Visual System I Intraframe mode (in MPEG) JPEG Joint Photographic Experts Group KLT Karhunen Lo eve Transform LB Leaky Bucket MPEG Moving Pictures Experts Group MR Multiresolution MSE Mean Squared Error P Prediction mode (in MPEG) PSNR Peak Signal to Noise Ratio R-D Rate{Distortion SBC Subband Coding SMG Statistical Multiplexing Gain

Robust Color Images Watermarking Using New Fractional-Order Exponent Moments

Abstract: Robust watermarking is a valuable methodology used in protecting the copyright and securing digital images. In this paper, new fractional-order multi-channel orthogonal exponent moments (MFrEMs) and their invariants to geometric transformations are derived for the first time. We utilized these highly accurate moments to construct a new robust watermarking algorithm for color images. This algorithm consists of three phases. First, the bits of the binary watermark scrambled by using a 1D Sine chaotic map. Second, the fractional-order MFrEMs are calculated from the host color image. Finally, a quantization process is performed, where the scrambled bits of the binary watermark embedded into the host color image. Various experiments were conducted to test the proposed watermarking algorithm and compare it with the existing robust watermarking algorithms for color images. The obtained results ensure the proposed robust watermarking algorithm’s superiority over existing algorithms regarding the visual imperceptibility and robustness against various attacks.

Coding of scene cuts in video sequences using non-reference frames

Abstract: A coding scheme for groups of frames that include scene cuts causes frames before and after the scene cut to be coded as non-reference frames with increased quantization parameters to reduce bandwidth. Although greater coding distortion can be expected for such frames, the distortion should be less or even not perceptible to a viewer owing to the dynamically changing image content caused by the scene change. Quantization parameter increases may vary based on: a viewing rate expected at a decoder, proximity of a frame to the scene cut, and observable motion speed both before and after the scene cut. Additionally, non-reference frames in the GOF may be coded using spatial direct mode coding.

JPEG Quantization Table Design for Face Images and Its Application to Face Recognition

Abstract: This paper proposes a new codec design method based on JPEG for face images and presents its application to face recognition. Quantization table is designed using the R-D optimization for the Yale face database. In order to use in the embedded systems, fast codec design is also considered. The proposed codec achieves better compression rates than JPEG codec for face images. In face recognition experiments using the linear discriminant analysis (LDA), the proposed codec shows better performance than JPEG codec.

Secure blind image steganographic technique using discrete Fourier transformation

Abstract: We present a new steganographic technique for covert communications. The technique embeds the hidden information in the DFT domain after permuting the image pixels in the spatial domain using a key. The permutation process introduces randomness into the cover image and results in a significant increase in the number of transform coefficients that can be used to transmit the hidden information. The hidden information is embedded using a quantization technique. The perceptual and statistical properties of the cover and the stego images remain similar for small quantization steps. The security of the system is examined against known stego attack.