Discrete Cosine Transform Domain Research Articles

System identification at an extremely low SNR using energy density in DCT domain

This paper presents a new approach for system identification at an extremely low signal-to-noise ratio (SNR) like -10 dB. At such a low SNR, many of the system peaks in the signal spectrum are indistinguishable from the noise peaks that lead to erroneous identification of system poles. In the proposed method, the system properties like energy density in discrete cosine transform (DCT) domain, which is less susceptible to noise even at such a low SNR, has been utilized to estimate autocorrelation function. Successive autocorrelations of this estimated function are taken for sequential identification of system parameters.

A Multiplicative Watermark Detection Algorithm for Digital Images in the DCT Domains

Watermark detection plays a crucial role in digital watermarking. It has traditionally been tackled using correlation-based techniques. However, correlation-based detection is not the optimum choice either when the host media doesn't follow a Gaussian distribution or when the watermark is not embedded in the host media in an additive way. This paper addresses the problem of DCT (discrete cosine transform) domain multiplicative watermark detection for digital images. First, generalized Gaussian distributions are applied to statistically model the AC (alternative current) DCT coefficients of the original image. Then, the imperceptibility constraint of watermarking is exploited, and watermark detection is formulated as the problem of weak signal detection in non-Gaussian noise. A binary hypothesis test concerning whether or not an image is watermarked is established, and an optimum detection structure for blind watermark detection is derived. Experimental results indicate the superiority of the new detector in the case that the embedding strengths are unknown to the detector. Therefore, the proposed detector can be used for the copyright protection of the digital multimedia data.

Arbitrary resizing of images in DCT domain using lapped transforms

An arbitrary L/M-fold image resizing method using lapped transforms is presented. The resizing operation is carried out in the lapped transform domain, by converting the images in the discrete cosine transform (DCT) domain into those in the lapped transform domain and vice versa. The proposed method provides visually fine images, while reducing the blocking effect to a very low level for images compressed at low bit rates.

Wavelet-based denoising attack on image watermarking

In this paper, we propose wavelet-based denoising attack methods on image watermarking in discrete cosine transform (DCT) or discrete Fourier transform (DFT) domain or discrete wavelet transform (DWT) domain. Wiener filtering based on wavelet transform is performed in approximation subband to remove DCT or DFT domain watermark, and adaptive wavelet soft thresholding is employed to remove the watermark resided in detail subbands of DWT domain.

Local discrete cosine transformation domain Volterra prediction of chaotic time series

In this paper a local discrete cosine transformation (DCT) domain Volterra prediction method is proposed to predict chaotic time series, where the DCT is used to lessen the complexity of solving the coefficient matrix. Numerical simulation results show that the proposed prediction method can effectively predict chaotic time series and improve the prediction accuracy compared with the traditional local linear prediction methods.

Video Extraction for Fast Content Access to MPEG Compressed Videos

As existing video processing technology is primarily developed in the pixel domain yet digital video is stored in compressed format, any application of those techniques to compressed videos would require decompression. For discrete cosine transform (DCT)-based MPEG compressed videos, the computing cost of standard row-by-row and column-by-column inverse DCT (IDCT) transforms for a block of 8/spl times/8 elements requires 4096 multiplications and 4032 additions, although practical implementation only requires 1024 multiplications and 896 additions. In this paper, we propose a new algorithm to extract videos directly from MPEG compressed domain (DCT domain) without full IDCT, which is described in three extraction schemes: 1) video extraction in 2/spl times/2 blocks with four coefficients; 2) video extraction in 4/spl times/4 blocks with four DCT coefficients; and 3) video extraction in 4/spl times/4 blocks with nine DCT coefficients. The computing cost incurred only requires 8 additions and no multiplication for the first scheme, 2 multiplication and 28 additions for the second scheme, and 47 additions (no multiplication) for the third scheme. Extensive experiments were carried out, and the results reveal that: 1) the extracted video maintains competitive quality in terms of visual perception and inspection and 2) the extracted videos preserve the content well in comparison with those fully decompressed ones in terms of histogram measurement. As a result, the proposed algorithm will provide useful tools in bridging the gap between pixel domain and compressed domain to facilitate content analysis with low latency and high efficiency such as those applications in surveillance videos, interactive multimedia, and image processing.

An Efficient Method for DCT-Domain Separable Symmetric 2-D Linear Filtering

We propose an efficient method for separable symmetric linear filtering in the discrete cosine transform (DCT) domain. First, separable two-dimensional (2-D) linear filtering is decomposed into the cascade of one-dimensional filtering in the DCT domain. We investigate special characteristics of DCT domain filtering matrices when the filter coefficients are symmetric. Then we present the DCT-domain 2-D filtering method using these characteristics. The proposed method requires a smaller number of multiplications including the typical sparseness of DCT coefficients compared to previous DCT-domain linear filtering methods. Also, the proposed method is composed of simple and regular operations, which would be appropriate for efficient very large scale integration implementation.

Adaptive reconstruction technique for the lost information of the rectangular image area

The adaptive reconstruction for the lost information of the rectangular image area is very important for the robust transmission and restoration of the image. In this paper, a new reconstruction method based on the Discrete Cosine Transform (DCT) domain has been put forward. According to the low pass character of the human visual system and the energy distribution of the DCT coefficients on the rectangular boundary, the DCT coefficients of the rectangular image area are adaptively selected and recovered. After the Inverse Discrete Cosine Transform (IDCT), the lost information of the rectangular image area can be reconstructed. The experiments have demonstrated that the subjective and objective qualities of the reconstructed images are enhanced greatly than before.

Fast wave-front reconstruction by solving the Sylvester equation with the alternating direction implicit method

Large degree-of-freedom real-time adaptive optics (AO) control requires reconstruction algorithms that are computationally efficient and readily parallelized for hardware implementation. In particular, we find the wave-front reconstruction for the Hudgin and Fried geometry can be cast into a form of the well-known Sylvester equation using the Kronecker product properties of matrices. We derive the filters and inverse filtering formulas for wave-front reconstruction in two-dimensional (2-D) Discrete Cosine Transform (DCT) domain for these two geometries using the Hadamard product concept of matrices and the principle of separable variables. We introduce a recursive filtering (RF) method for the wave-front reconstruction on an annular aperture, in which, an imbedding step is used to convert an annular-aperture wave-front reconstruction into a squareaperture wave-front reconstruction, and then solving the Hudgin geometry problem on the square aperture. We apply the Alternating Direction Implicit (ADI) method to this imbedding step of the RF algorithm, to efficiently solve the annular-aperture wave-front reconstruction problem at cost of order of the number of degrees of freedom, O(n). Moreover, the ADI method is better suited for parallel implementation and we describe a practical real-time implementation for AO systems of order 3,000 actuators.

Digital watermarking-based DCT and JPEG model

In recent years, digital watermarking techniques have been proposed to protect the copyright of multimedia data. Different watermarking schemes have been suggested for images. The goal of this paper is to develop a watermarking algorithm based on the discrete cosine transform (DCT) and image segmentation. The image is first segmented in different portions based on the Voronoi diagram and features extraction points. Then, a pseudorandom sequence of real numbers is embedded in the DCT domain of each image segment. Different experiments are conducted to show the performance of the scheme under different types of attacks. The results show that our proposed watermark scheme is robust to common signal distortions, including geometric manipulations. The robustness against Joint Photographic Experts Group (JPEG) compression is achieved for a compression ratio of up to 45, and robustness against average, median, and Wiener filters is shown for the 3/spl times/3 up to 9/spl times/9 pixel neighborhood. It is observed that robustness against scaling was achieved when the watermarked image size is scaled down to 0.4% of its original size.

L/M-fold image resizing in block-dct domain using symmetric convolution

Image resizing is to change an image size by upsampling or downsampling of a digital image. Most still images and video frames on digital media are given in a compressed domain. Image resizing of a compressed image can be performed in the spatial domain via decompression and recompression. In general, resizing of a compressed image in a compressed domain is much faster than that in the spatial domain. We propose a novel approach to resize images with L/M resizing ratio in the discrete cosine transform (DCT) domain, which exploits the multiplication-convolution property of DCT (multiplication in the spatial domain corresponds to symmetric convolution in the DCT domain). When an image is given in terms of its 8 x 8 block-DCT coefficients, its resized image is also obtained in 8 x 8 block-DCT coefficients. The proposed approach is computationally fast and produces visually fine images with high PSNR.

Fast loop filtering using separable characteristics of the integer 2-D discrete cosine transform

When an image is highly compressed, video coding using the discrete cosine transform (DCT) and quantization produces noticeable image degradations, such as blocking artifacts and ringing noise. In order to reduce the degradations, a loop filtering algorithm is proposed, which consists of simple deblocking filtering and a fast decision rule for ringing and blocking conditions. The proposed method utilizes a four-point integer DCT for detecting blocking and ringing conditions. It also adopts an early termination policy during detection of the blocking and ringing conditions in the DCT domain. This policy speeds up computation of the filtering. The proposed method is compared with the loop filtering of the Joint Video Team (JVT) codec. As an experimental result, the computation time of the proposed method is approximately 20% faster than that of the JVT loop filtering, while the PSNR is almost the same.

A contrast based image fusion technique in the DCT domain

This paper studies image fusion techniques in the discrete cosine transform (DCT) domain. A new image fusion technique based on a contrast measure defined in the DCT domain is presented. The performance of our contrast measure based technique is analyzed and compared with other image fusion techniques. Experimental results show that there is no difference in visual quality between the fused image obtained by our algorithm and that obtained by a wavelet transform based image fusion technique. But because our algorithm is carried out in the DCT domain, it is time-saving and simpler when the fused image needs to be saved or transmitted in JPEG format or when the images to be fused were saved in JPEG format.

Boundary effect free and adaptive discrete signal sinc-interpolation algorithms for signal and image resampling.

The problem of digital signal and image resampling with discrete sinc interpolation is addressed. Discrete sine interpolation is theoretically the best one among the digital convolution-based signal resampling methods because it does not distort the signal as defined by its samples and is completely reversible. However, sinc interpolation is frequently not considered in applications because it suffers from boundary effects, tends to produce signal oscillations at the image edges, and has relatively high computational complexity when irregular signal resampling is required. A solution that enables the elimination of these limitations of the discrete sine interpolation is suggested. Two flexible and computationally efficient algorithms for boundary effects free and adaptive discrete sinc interpolation are presented: frame-wise (global) sine interpolation in the discrete cosine transform (DCT) domain and local adaptive sinc interpolation in the DCT domain of a sliding window. The latter offers options not available with other interpolation methods: interpolation with simultaneous signal restoration/enhancement and adaptive interpolation with super resolution.

Asymptotically optimal detection for additive watermarking in the DCT and DWT domains

Most of the watermarking schemes that have been proposed until now employ a correlation detector (matched filter). The current paper proposes a new detector scheme that can be applied in the case of additive watermarking in the DCT (discrete cosine transform) or DWT (discrete wavelet transform) domain. Certain properties of the probability density function of the coefficients in these domains are exploited. Thus, an asymptotically optimal detector is constructed based on well known results of the detection theory. Experimental results prove the superiority of the proposed detector over the correlation detector.

Real-time foveation techniques for low bit rate video coding

Lossy video compression methods often rely on modeling the abilities and limitations of the intended receiver, the human visual system (HVS), to achieve the highest possible compression with as little effect on perceived quality as possible. Foveation, which is non-uniform resolution perception of the visual stimulus by the HVS due to the non-uniform density of photoreceptor cells in the eye, has been demonstrated to be useful for reducing bit rates beyond the abilities of uniform resolution video coders. In this work, we present real-time foveation techniques for low bit rate video coding. First, we develop an approximate model for foveation. Then, we demonstrate that foveation, as described by this model, can be incorporated into standard motion compensation and discrete cosine transform (DCT)-based video coding techniques for low bit rate video coding, such as the H.263 or MPEG-4 video coding standards, without incurring prohibitive complexity overhead. We demonstrate that foveation in the DCT domain can actually result in computational speed-ups. The techniques presented can be implemented using the baseline modes in the video coding standards and do not require any modification to, or post-processing at, the decoder.

Image extraction in DCT domain

More and more digital images are being stored in compressed formats, among which the format using discrete cosine transform (DCT) coefficients is widely adopted (JPEG, MPEG, H.263 etc). To exploit those successful image processing techniques developed in the pixel domain, the authors propose a fast image extraction algorithm to allow images to be extracted directly from compressed DCT coefficients without full decompression. In the proposed technique the extracted images retain quality comparable with that of fully decoded images. However, the computing cost and the storage expense incurred by the proposed algorithm are very much lower than the costs of full decompression. The experiments also demonstrate that the proposed algorithm has tremendous potential in that all existing image processing techniques developed in the pixel domain can be directly applied to compressed images, without involving full decompression.

Robustness investigation of DCT digital watermark for printing and scanning

AbstractThis paper reports the effect of printing and scanning on digital watermarks for a hard copy image and investigates the necessary conditions for the watermark to be robust against the printing and scanning process. The effect of the printing and scanning process on the image content is presented first, and that on the Discrete Cosine Transform (DCT) domain is discussed next. Thus, we have necessary conditions for the watermark to be robust and present a sufficient condition to construct robust watermarking. It is realized by decreasing mutual interference between the embedded elements. This will enable us to make image content common to both the electrical nets and the physical nets. © 2002 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 86(4): 11–19, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjc.10059

Efficient DCT-domain blind measurement and reduction of blocking artifacts

Blocking artifacts continue to be among the most serious defects that occur in images and video streams compressed to low bit rates using block discrete cosine transform (DCT)-based compression standards (e.g., JPEG, MPEG, and H.263). It is of interest to be able to numerically assess the degree of blocking artifact in a visual signal, for example, in order to objectively determine the efficacy of a compression method, or to discover the quality of video content being delivered by a web server. We propose new methods for efficiently assessing, and subsequently reducing, the severity of blocking artifacts in compressed image bitstreams. The method is blind, and operates only in the DCT domain. Hence, it can be applied to unknown visual signals, and it is efficient since the signal need not be compressed or decompressed. In the algorithm, blocking artifacts are modeled as 2-D step functions. A fast DCT-domain algorithm extracts all parameters needed to detect the presence of, and estimate the amplitude of blocking artifacts, by exploiting several properties of the human vision system. Using the estimate of blockiness, a novel DCT-domain method is then developed which adaptively reduces detected blocking artifacts. Our experimental results show that the proposed method of measuring blocking artifacts is effective and stable across a wide variety of images. Moreover, the proposed blocking-artifact reduction method exhibits satisfactory performance as compared to other post-processing techniques. The proposed technique has a low computational cost hence can be used for real-time image/video quality monitoring and control, especially in applications where it is desired that the image/video data be processed directly in the DCT-domain.

Motion vector refinement for video downsampling in the DCT domain

This letter presents a fast motion vector refinement (MVR) for video downsampling in the discrete cosine transform (DCT) domain. To reduce the computational complexity of the MVR, we propose a fast search algorithm, based on minimizing the number of required checkpoints, and a computationally efficient method for extracting the motion-compensated DCT (MC-DCT) block. Compared to the known extraction method of the MC-DCT block, the proposed method requires fewer than one-half the multiplications and additions.