• The Journal of the Acoustical Society of Korea
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• v.32 no.6
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• pp.525-531
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• 2013

In this paper, we propose to apply low delay algorithm using power complementary window to Integer Modified Discrete Cosine Transform (IntMDCT). Conventional transform, the Modified Discrete Cosine Transform (MDCT) usually produces floating point values for integer input values. This causes the expansion of the data. To refine on this, IntMDCT that produces integer values even for integer input values have emerged. However, IntMDCT has a problem of the algorithm delay, such as MDCT. Delay has became a key issue in environments for the purpose of real-time communications. In order to reduce the delay, the proposed algorithm was applied and the results of the performance evaluation show that delay of IntMDCT has reduced by halfexisting delay.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.538-541
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• 1999

MPEG-2 AAC(Advanced Audio Coding) is the most advanced coding scheme available for high quality audio coding. This MPEG-2 AAC audio Standard allows for ITU-R ‘indistinguishable’ quality according to at data rates of 320 kb/s for five full-bandwidth channel audio signals. The compression ratio is around a factor of 1.4 better compared to MPEG Layer 3, you get the same quality at 70% of the bitrate. This paper suggest optimization method for MDCT/IMDCT (Modified Discrete Cosine Transform/Inverse Modified Discrete Cosine Transform) in Encoder and Decoder for AAC.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.329-332
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• 1999

Currently, the most important technology is compression methods in the multimedia society. In audio compression, the method using human auditory nervous property is used. This method using psychoacoustical model is applied to perceptual audio coding, because human's audibility is limited. MPEG-II AAC(Advanced Audio Coding) is the most advanced coding scheme that is of benefit to high quality audio coding. The compression ratio is 1.4 times compared with MPEG-I layer-III. In this paper, the vector processor for MDCT/IMDCT(Modified Discrete Cosine Transform /Inverse Modified Discrete Cosine Transform) of MPEG-II AAC is designed.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.69-73
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• 2003

음향압축에 있어서 인간의 청각신경의 특성을 이용하는 방식이 사용되고 있다. 이러한 방법은 심리음향모델(psychoacustical model)에서 도입되었다. 음향압축에서는 이러한 심리음향모델을 사용하여 인간이 지각할 수 없는 한도 내에서 부호화하지 않는 지각음향부호화(perceptual audio coding)사용한다. 지각음향부호화는 분석필터와 합성필터로 각각 부호화 복호화하는데 이것은 필터뱅크(filter bank)로 구현된 서브밴드코더(subband coder) 이다. 본 논문에서는 분석필터와 합성필터에 사용되는 MDCT(Modified Discrete Cosine Transform)와 IMDCT(Inverse Modified Discrete Cosine Transform)를 FPGA에 구현하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4448-4466
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• 2018

In recent years, due to its high efficiency and better performance, the high efficiency video coding (HEVC) has become the most common compression standard in the field of video coding. In this paper, the framework of HEVC is deeply analyzed, and an improved HEVC video coding algorithm based on all phase biorthogonal transform (APBT) is proposed, where APBT is utilized to replace the discrete cosine transform (DCT) and discrete sine transform (DST) in original HEVC standard. Based on the relationship between APBT and DCT, the integer APBT is deduced. To further improve the coding performance, an optimal HEVC video coding algorithm based on hybrid APBT is proposed. The coding performance of the proposed HEVC coding algorithm is improved without increasing the complexity. Experimental results show that compared with HEVC standard algorithm, the improved HEVC video coding algorithm based on hybrid APBT can improve the coding performance of chrominance components by about 0.3%.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.754-764
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• 2016

The exhaustive list of sparsification methods for a digital image suffers from achieving an adequate number of zero and near-zero coefficients. The method proposed in this paper, which is known as the Discrete Rajan Transform Sparsification, overcomes this inadequacy. An attempt has been made to compare the simulation results for benchmark images by various popular, existing techniques and analyzing from different aspects. With the help of Discrete Rajan Transform algorithm, both lossless and lossy sparse representations are obtained. We divided an image into $8{\times}8-sized$ blocks and applied the Discrete Rajan Transform algorithm to it to get a more sparsified spectrum. The image was reconstructed from the transformed output of the Discrete Rajan Transform algorithm with an acceptable peak signal-to-noise ratio. The performance of the Discrete Rajan Transform in providing sparsity was compared with the results provided by the Discrete Fourier Transform, Discrete Cosine Transform, and the Discrete Wavelet Transform by means of the Degree of Sparsity. The simulation results proved that the Discrete Rajan Transform provides better sparsification when compared to other methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2407-2414
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• 1999

This paper introduces the concept of warped discrete cosine transform (WDCT) and an image compression algorithm based on the WDCT. The proposed WDCT is a cascade connection of a conventional DCT and all-pass filters whose parameters can be adjusted to provide frequency warping. In the proposed image compression scheme, the frequency response of the all-pass filter is controlled by a set of parameters with each parameter for a specified frequency range. For each image block, the best parameter is chosen from the set and is sent to the decoder as a side information along with the result of corresponding WDCT computation. For actual implementation, the combination of the all-pass IIR filters and the DCT can be viewed as a cascade of a warping matrix and the DCT matrix, or as a filter bank which is obtained by warping the frequency response of the DCT filter bank. Hence, the WDCT can be implemented by a single matrix computation like the DCT. The WDCT based compression, outperforms the DCT based compression, for high bit rate applications and for images with high frequency components.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.6
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• pp.106-113
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• 2003

The modified discrete cosine transform (MDCT) and inverse MDCT (IMDCT) are employed in subband/transform coding schemes as the analysis/synthesis filter bank based on time domain aliasing cancellation (TDAC). And the MDCT and IMDCT are the most computational intensive operations in layer III of the MPEG audio coding standard. In this paper, we propose a new efficient algorithm for the MDCT/IMDCT computation in various audio coding systems. It is based on the MDCT/IMDCT computation algorithm using the discrete cosine transforms (DCTs), and It employs two discrete cosine transform of type II (DCT-II) to compute the MDCT/IMDCT In addition, it takes advantage of ability in calculating the MDCT/IMDCT computation, where the length of a data block Is divisible by 4. The Proposed algorithm in this paper requires less calculation complexity than the existing method does. Also, it can be implemented by the parallel structure, therefore its structure is particularly suitable for VLSI realization

• Journal of KIISE:Information Networking
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• v.30 no.1
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• pp.17-23
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• 2003

In this Paper. we Propose a digital watermarking scheme for digital images based on a perceptual model, the frequency masking, texture making, and luminance masking Properties of the human visual system(HVS), which have been developed in the context of image compression. We embed two types of watermark, one is pseudo random(PN) sequences, the other is a logo image. To embed the watermarks, original images are decomposed into $8\times8$ blocks, and the discrete cosine transform(DCT) is carried out for each block. Watermarks are casted in the low frequency components of DCT coefficients. The perceptual model adjusts adaptively scaling factors embedding watermarks according to the local image properties. Experimental results show that the proposed scheme presents better results than that of non-perceptual watermarking methods for image qualify without loss of robustness.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.3
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• pp.97-103
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• 2008

In this paper, $256{\times}256$ input image is classified into a validity block and an edge block of $8{\times}8$ block for image compression. DCT(Discrete Cosine Transform) is executed only for the DC coefficient that is validity coefficients for a validity block. Predict the position where a quantization coefficient becomes 0 for an edge block, I propose new algorithm to execute DCT in the reduced region. Not only this algorithm that I proposed reduces computational complexity of FDCT(Forward DCT) and IDCT(Inverse DCT) and decreases encoding time and decoding time. I let compressibility increase by accomplishing other stability verticality zigzag scan by the block size that was classified for each block at the time of huffman encoding each. In addition, the algorithm that I suggested reduces Run-Length by accomplishing the level verticality zigzag scan that is good for a classified block characteristic and, I offer the compressibility that improved thereby.