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Modified discrete cosine transform

About: Modified discrete cosine transform is a research topic. Over the lifetime, 1453 publications have been published within this topic receiving 30211 citations. The topic is also known as: Modified Discrete Cosine Transform, MDCT.


Papers
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01 Jan 2009
TL;DR: This paper introduces an algorithm of digital watermarking based on Discrete Cosine Transform and Discrete Wavelet Transform which is invisible and has good robustness for some common image processing operations.
Abstract: This paper introduces an algorithm of digital watermarking based on Discrete Cosine Transform(DCT) and Discrete Wavelet Transform(DWT). Accoring to the characters of human vision, in this algorithm, the information of digital watermarking which has been discrete Cosine transformed, is put into the high frequency band of the image which has been wavelet transformed. Then distills the digital watermarking with the help of the original image and the watermarking image. The simulation results show that this algorithm is invisible and has good robustness for some common image processing operations.

199 citations

Journal ArticleDOI
01 Aug 1989
TL;DR: In this paper, the authors show how to convert the order-8 cosine transforms into a family of integer cosine transform (ICTs) using the theory of dyadic symmetry.
Abstract: The paper shows how to convert the order-8 cosine transforms into a family of integer cosine transforms (ICTs) using the theory of dyadic symmetry. The new transforms can be implemented using simple integer arithmetic. It was found that performance close to that of the DCT can be achieved with an ICT that requires only 4 bits for representation of its kernel com- ponent magnitude. Better performance can be achieved by some ICTs whose kernel components require longer bit lengths for representation. ICTs that require 3 bits or less for representation of their component magnitude are available but with degraded performance. The availability of many ICTs provides an engineer the freedom to tradeoff performance for simple implementation in design- ing a transform codec.

163 citations

Book
01 Jan 1966

161 citations

Proceedings Article
01 Sep 2005
TL;DR: This paper presents a new robust hybrid watermarking scheme based on DCT and SVD, and shows that embeddingData in lowest frequencies is resilient to one set of attacks while embedding data in highest frequencies is resilience to another set of Attacks.
Abstract: Both Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD) have been used as mathematical tools for embedding data into an image. In this paper, we present a new robust hybrid watermarking scheme based on DCT and SVD. After applying the DCT to the cover image, we map the DCT coefficients in a zig-zag order into four quadrants, and apply the SVD to each quadrant. These four quadrants represent frequency bands from the lowest to the highest. The singular values in each quadrant are then modified by the singular values of the DCT-transformed visual watermark. We assume that the size of the visual watermark is one quarter of the size of the cover image. We show that embedding data in lowest frequencies is resilient to one set of attacks while embedding data in highest frequencies is resilient to another set of attacks. We compare our hybrid algorithm with a pure SVD-based scheme.

161 citations

Patent
18 Sep 1991
TL;DR: In this article, a method for processing a field of image data samples to provide for one or more of the functions of decimation, interpolation, and sharpening is accomplished by use of an array transform processor such as that employed in a JPEG compression system.
Abstract: A method for processing a field of image data samples to provide for one or more of the functions of decimation, interpolation, and sharpening is accomplished by use of an array transform processor such as that employed in a JPEG compression system. Blocks of data samples are transformed by the discrete even cosine transform (DECT) in both the decimation and interpolation processes, after which the number of frequency terms is altered. In the case of decimation, the number of frequency terms is reduced, this being followed by inverse transformation to produce a reduced-size matrix of sample points representing the original block of data. In the case of interpolation, additional frequency components of zero value are inserted into the array of frequency components after which inverse transformation produces an enlarged data sampling set without an increase in spectral bandwidth. In the case of sharpening, accomplished by a convolution or filtering operation involving multiplication of transforms of data and filter kernel in the frequency domain, there is provided an inverse transformation resulting in a set of blocks of processed data samples. The blocks are overlapped followed by a savings of designated samples, and a discarding of excess samples from regions of overlap. The spatial representation of the kernel is modified by reduction of the number of components, for a linear-phase filter, and zero-padded to equal the number of samples of a data block, this being followed by forming the discrete odd cosine transform (DOCT) of the padded kernel matrix.

156 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20236
202218
20217
20207
20199
201816