• The KIPS Transactions:PartD
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• v.17D no.6
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• pp.463-470
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• 2010

We presented a very fast and robust method of text line segmentation based on the DCT blocks of color image without decompression and binary transformation processes. Using DC and another three primary AC coefficients from block DCT we created a gray-scale image having reduced size by 8x8. In order to detect and locate white strips between text lines we analyzed horizontal and vertical projection profiles of the image and we applied a direct markov model to recover the missing white strips by estimating hidden periodicity. We presented performance results. The results showed that our method was 40 - 100 times faster than traditional method.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1383-1386
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• 1997

Discrete cosine transform(DCT) is the most popular block transform coding in lossy mode. DCT is close to statistically optimal transform-the Karhunen Loeve transform. In this paper, a module for DCT encoder is made with TMS320C80 based on JPEG and MPEG, which are intermational standards for image compression. the DCT encoder consists of three parts-a transformer, a vector quantizer and an entropy encoder.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2351-2354
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• 2003

A new transform coder for arbitrarily shaped image segments is proposed. In the encoder, a block-based DCT is applied to the resulting image block after shifting pixels within the image segment to block border and padding the mean value of the pixels to empty region. For reducing the transmission bit rate, the transform coefficients located in padded region are truncated and only the remaining transform coefficients are transmitted to the decoder. In the decoder, the transform coefficients truncated in the encoder are recovered using received transform coefficients and a block-based inverse DCT is performed.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.863-866
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• 1998

In this paper, we proposes Moving Picture Compression reducing bit numbers within the block by probability in 3D-DCT considered of temporal axis. From Delta Modification theory for frequency components, bit numbers within the block(4$\times$4) were properly compressed by using the Probability Entropy. At the result for the proposed algorithm, we could find that the values of PSNR for resolution and the compression rate were better than existing methods.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.913-914
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• 2008

This paper presents a method of adaptive image enhancement with dynamic range compression and contrast enhancement. The dynamic range compression is to adaptively enhance the dark area using illumination component of DCT compression block. The contrast enhancement is to modify the image contrast using retinex theory that uses the HVS properties. The block artifacts and other noises, caused by processing in the compression domain, were removed by after processing.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.6
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• pp.1005-1012
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• 1987

An adaptive scalar DCT-Wiener filtering method that can be applied to the problem of restoring an image degraded by white Gaussian noise is presented. In this method, the power spectrum needed to Winer filering is adaptively estimated in block-wise according to the lical properties in transform domain. In addition, overlapping method for reducing the block artifact is considered. Experimental results show that the adaptive Wiener filter by the proposed method yields performance improvement and better image quality over the nonadaptive one and the spatial Lee filter.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.1
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• pp.20-26
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• 2013

Image noise reduction in the frequency domain by thresholding is simple, but quite effective. Wavelet domain thresholding has been an active area of research but relatively little work has been published on DCT domain denoising. A novel method for determining the hard threshold for the DCT domain denoising is proposed. The low amplitude DCT coefficients are discarded until the cumulative sum of the discarded signal energy is comparable to that of noise in each DCT block. Cycle spinning is also applied to reduce block artifacts. The proposed method is quite effective and simple enough to be used in portable devices.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.901-910
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• 2004

In this paper, we propose a content-based MPEG transcoding method using a discontinuity feature in the Discrete Cosine Transform (DCT) domain. A DCT block is transcoded differently depending on the height of dominant discontinuity within a block. In the experiment, we show the result that the video quality of content-based transcoding is better than that of a constant cut-off method and the processing time of the adaptive method is much faster compared with the pixel domain methods in the same bandwidth.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.107-110
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• 2018

Image compression is the application of Data compression on digital images. The (DCT) discrete cosine transform is a technique for converting a time domain to a frequency domain. It is widely used in image compression. First, the image is divided into 8x8 pixel blocks. Apply the DCT to each block while processing from top to bottom from left to right. Each block is compressed through quantization. The space of the compressed block array constituting the image is greatly reduced. Reconstruct the image through the IDCT. The purpose of this research is to understand compression/decompression of images using the DCT method.

• Journal of IKEEE
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• v.2 no.1 s.2
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• pp.96-100
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• 1998

Due to expected wide spread use of DCT based image/video coding standard, it is advantageous to process data directly in the DCT domain rather than decoding the source back to the spatial domain. The block processing algorithm provides a parallel processing method since multiple input data are processed in the block filter structure. Hence a fast implementation of the algorithm is well suited. In this paper, we propose the JPEG browse by Block Transform Domain Filtering(BTDF) using subband filter banks. Instead of decompressing the entire image to retrieve at full resolution from compressed format, a user can select the level of expansion required$(2^N{\times}2^N)$. Also this approach reduces the computer cpu time by reducing the number of multiplication through BTDF in the filter banks.