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.

Hierarchical encoding method and apparatus for efficiently communicating image sequences

Abstract: A method and apparatus for encoding interframe error data in an image transmission system, and in particular in a motion compensated image transmission system for transmitting a sequence of image frames from a transmitter to a receiver, employ hierarchial vector quantization and arithmetic coding to increase the data compression of the images being transmitted. The method and apparatus decimate an interframe predicted image data and an uncoded current image data, and apply hierarchial vector quantization encoding to the resulting pyramid data structures. Lossy coding is applied on a level-by-level basis for generating the encoded data representation of the image difference between the predicted image data and the uncoded original image. The method and apparatus are applicable to systems transmitting a sequence of image frames both with and without motion compensation. The method and apparatus feature blurring those blocks of the predicted image data which fail to adequately represent the current image at a pyramid structural level and shifting block boundaries to increase the efficiency of the vector quantization coding mechanism. The method further features techniques when gain/shape vector quantization is employed for decreasing the data which must be sent to the receiver by varying the size of the shape code book as a function of the gain associated with the shape. Thresholding and the deletion of isolated blocks of data also decrease transmission requirements without objectionable loss of image quality.

A content-based image retrieval scheme in jpeg compressed domain

Abstract: Nowadays, a large number of images are compressed in JPEG (Joint Photo- graphic Experts Group) format. Therefore, content-based image retrieval (CBIR) for the JPEG images has attracted many people's attention and a series of algorithms directly based on the discrete cosine transform (DCT) domain have been proposed. However, the existing methods are far from the practical application. Thus, in this paper, a new image retrieval scheme for JPEG formatted images is presented. The color, spatial and frequency (texture) features based on the DCT domain are extracted for the later image retrieval. It doesn't require decompressing the images but directly retrieving in the DCT domain. Thus, compared with the spatial domain based retrieval methods for JPEG im- ages, the computation complexity can be greatly reduced. In addition, this retrieval system is suitable for all color images with different sizes. Experimental results demonstrate the advantages of the proposed retrieval scheme.

Assessing the performance of a method of simultaneous compression and encryption of multiple images and its resistance against various attacks

Abstract: We introduce a double optimization procedure for spectrally multiplexing multiple images. This technique is adapted from a recently proposed optical setup implementing the discrete cosine transformation (DCT). The new analysis technique is a combination of spectral fusion based on the properties of DCT, specific spectral filtering, and quantization of the remaining encoded frequencies using an optimal number of bits. Spectrally multiplexing multiple images defines a first level of encryption. A second level of encryption based on a real key image is used to reinforce encryption. A set of numerical simulations and a comparison with the well known JPEG (Joint Photographic Experts Group) image compression standard have been carried out to demonstrate the improved performances of this method. The focus here will differ from the method of simultaneous fusion, compression, and encryption of multiple images (SFCE) [Opt. Express 19, 24023 (2011)] in the following ways. Firstly, we shall be concerned with optimizing the compression rate by adapting the size of the spectral block to each target image and decreasing the number of bits required to encode each block. This size adaptation is achieved by means of the root-mean-square (RMS) time-frequency criterion. We found that this size adaptation provides a good tradeoff between bandwidth of spectral plane and number of reconstructed output images. Secondly, the encryption rate is improved by using a real biometric key and randomly changing the rotation angle of each block before spectral fusion. By using a real-valued key image we have been able to increase the compression rate of 50% over the original SFCE method. We provide numerical examples of the effects for size, rotation, and shifting of DCT-blocks which play noteworthy roles in the optimization of the bandwidth of the spectral plane. Inspection of the results for different types of attack demonstrates the robustness of our procedure.

An efficient JPEG steganographic scheme based on the block entropy of DCT coefficients

Abstract: Steganography is the art of covert communication. This paper presents an efficient JPEG steganography scheme based on the block entropy of DCT coefficients and syndrome trellis coding (STC). The proposed cost function explores both the block complexity and distortion effects due to flipping and rounding errors. The STC provides multiple solutions to embed messages to a block of coefficients. The proposed scheme determines the best one with minimal distortion effect. In this way, the total distortions are significantly reduced, which corresponds to less detectability of steganalysis. Compared with similar schemes, experiment results demonstrate the superior performance of the proposed scheme in terms of secure embedding capacity against steganalysis.