A Fast Computational Algorithm for the Discrete Cosine Transform
TL;DR: A Fast Discrete Cosine Transform algorithm has been developed which provides a factor of six improvement in computational complexity when compared to conventional DiscreteCosine Transform algorithms using the Fast Fourier Transform.
Abstract: A Fast Discrete Cosine Transform algorithm has been developed which provides a factor of six improvement in computational complexity when compared to conventional Discrete Cosine Transform algorithms using the Fast Fourier Transform. The algorithm is derived in the form of matrices and illustrated by a signal-flow graph, which may be readily translated to hardware or software implementations.
Citations
More filters
TL;DR: A near real-time recognition system with 20 complex objects in the database has been developed and a compact representation of object appearance is proposed that is parametrized by pose and illumination.
Abstract: The problem of automatically learning object models for recognition and pose estimation is addressed. In contrast to the traditional approach, the recognition problem is formulated as one of matching appearance rather than shape. The appearance of an object in a two-dimensional image depends on its shape, reflectance properties, pose in the scene, and the illumination conditions. While shape and reflectance are intrinsic properties and constant for a rigid object, pose and illumination vary from scene to scene. A compact representation of object appearance is proposed that is parametrized by pose and illumination. For each object of interest, a large set of images is obtained by automatically varying pose and illumination. This image set is compressed to obtain a low-dimensional subspace, called the eigenspace, in which the object is represented as a manifold. Given an unknown input image, the recognition system projects the image to eigenspace. The object is recognized based on the manifold it lies on. The exact position of the projection on the manifold determines the object's pose in the image. A variety of experiments are conducted using objects with complex appearance characteristics. The performance of the recognition and pose estimation algorithms is studied using over a thousand input images of sample objects. Sensitivity of recognition to the number of eigenspace dimensions and the number of learning samples is analyzed. For the objects used, appearance representation in eigenspaces with less than 20 dimensions produces accurate recognition results with an average pose estimation error of about 1.0 degree. A near real-time recognition system with 20 complex objects in the database has been developed. The paper is concluded with a discussion on various issues related to the proposed learning and recognition methodology.
2,037 citations
TL;DR: An efficient general-purpose blind/no-reference image quality assessment (IQA) algorithm using a natural scene statistics model of discrete cosine transform (DCT) coefficients, which requires minimal training and adopts a simple probabilistic model for score prediction.
Abstract: We develop an efficient general-purpose blind/no-reference image quality assessment (IQA) algorithm using a natural scene statistics (NSS) model of discrete cosine transform (DCT) coefficients. The algorithm is computationally appealing, given the availability of platforms optimized for DCT computation. The approach relies on a simple Bayesian inference model to predict image quality scores given certain extracted features. The features are based on an NSS model of the image DCT coefficients. The estimated parameters of the model are utilized to form features that are indicative of perceptual quality. These features are used in a simple Bayesian inference approach to predict quality scores. The resulting algorithm, which we name BLIINDS-II, requires minimal training and adopts a simple probabilistic model for score prediction. Given the extracted features from a test image, the quality score that maximizes the probability of the empirically determined inference model is chosen as the predicted quality score of that image. When tested on the LIVE IQA database, BLIINDS-II is shown to correlate highly with human judgments of quality, at a level that is competitive with the popular SSIM index.
1,484 citations
TL;DR: The MorphoSys architecture is described, including the reconfigurable processor array, the control processor, and data and configuration memories, and the suitability of MorphoSy for the target application domain is illustrated with examples such as video compression, data encryption and target recognition.
Abstract: This paper introduces MorphoSys, a reconfigurable computing system developed to investigate the effectiveness of combining reconfigurable hardware with general-purpose processors for word-level, computation-intensive applications. MorphoSys is a coarse-grain, integrated, and reconfigurable system-on-chip, targeted at high-throughput and data-parallel applications. It is comprised of a reconfigurable array of processing cells, a modified RISC processor core, and an efficient memory interface unit. This paper describes the MorphoSys architecture, including the reconfigurable processor array, the control processor, and data and configuration memories. The suitability of MorphoSys for the target application domain is then illustrated with examples such as video compression, data encryption and target recognition. Performance evaluation of these applications indicates improvements of up to an order of magnitude (or more) on MorphoSys, in comparison with other systems.
895 citations
TL;DR: Note: V. Madisetti, D. B. Williams, Eds.
862 citations
Cites methods from "A Fast Computational Algorithm for ..."
...algorithms for its computation [51, 64 , 70, 72]....
[...]
01 Jan 1997
TL;DR: MadMadisetti, D. B. Williams, Eds. as discussed by the authors, LCAV-2005-009 Record created on 2005-06-27, modified on 2017-05-12
Abstract: Note: V. K. Madisetti, D. B. Williams, Eds. Reference LCAV-CHAPTER-2005-009 Record created on 2005-06-27, modified on 2017-05-12
839 citations
References
More filters
TL;DR: In this article, a discrete cosine transform (DCT) is defined and an algorithm to compute it using the fast Fourier transform is developed, which can be used in the area of digital processing for the purposes of pattern recognition and Wiener filtering.
Abstract: A discrete cosine transform (DCT) is defined and an algorithm to compute it using the fast Fourier transform is developed. It is shown that the discrete cosine transform can be used in the area of digital processing for the purposes of pattern recognition and Wiener filtering. Its performance is compared with that of a class of orthogonal transforms and is found to compare closely to that of the Karhunen-Loeve transform, which is known to be optimal. The performances of the Karhunen-Loeve and discrete cosine transforms are also found to compare closely with respect to the rate-distortion criterion.
4,481 citations
TL;DR: Two hybrid coding systems utilizing a cascade of a unitary transformation and differential pulse code modulators (DPCM) systems are proposed and the performance of this system is compared to the performances of the two- dimensional DPCM and the standard two-dimensional transform encoders.
Abstract: Two hybrid coding systems utilizing a cascade of a unitary transformation and differential pulse code modulators (DPCM) systems are proposed. Both systems encode the transformed data by a bank of DPCM systems. The first system uses a one-dimensional transform of the data where the second one employs two-dimensional transformations. Theoretical results for Markov data and experimental results for a typical picture are presented for Hadamard, Fourier, cosine, slant, and the KarhunenLoeve transformations. The visual effects of channel error and also the impact of noisy channel on the performance of the hybrid system, measured in terms of the signal-to-noise ratio of the encoder, is examined and the performance of this system is compared to the performances of the two-dimensional DPCM and the standard two-dimensional transform encoders.
136 citations
30 Oct 1975
TL;DR: This work addresses the individual error sources in transform image coding by separating the component of the MSE introduced by transform coefficient deletion is separated from requantization effects.
Abstract: The mean square error (MSE) is a classical measure of image distortion. However, this metric is generally not a faithful indication of subjective image quality. We attempt to correct this deficiency by addressing the individual error sources in transform image coding. Specifically, the component of the MSE introduced by transform coefficient deletion is separated from requantization effects. Results are demonstrated in both numerical and pictorial form.© (1975) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
9 citations