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Journal ArticleDOI

VLSI Implementation of Discrete Cosine Transform Approximation Recursive Algorithm

01 Mar 2021-Vol. 1817, Iss: 1, pp 012017
TL;DR: A general recursive algorithm is used here, and its length is obtained using DCT pairs of length N/2 of N addition cost in input pre-processing, to achieve the proposed approximation algorithm that is highly scalable to enforce the highest lengths software and hardware.
Abstract: In general, the approximation of Discrete Cosine Transform (DCT) is used to decrease computational complexity without impacting its efficiency in coding. Many of the latest algorithms used in DCT approximation functions have only a smaller DCT length transform of which some are non-orthogonal. For computing DCT orthogonal approximation, a general recursive algorithm is used here, and its length is obtained using DCT pairs of length N/2 of N addition cost in input pre-processing. The recursive sparse matrix has been decomposed by using the vector symmetry from the DCT basis in order to achieve the proposed approximation algorithm that is highly scalable to enforce the highest lengths software and hardware by using a current 8-point approximation to obtain a DCT approximation with two-length power, N>8.
Citations
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Journal ArticleDOI
TL;DR: In this article , an innovative method to obtain 2Dimensional images which are nearly lossless in compression using DCT (discrete cosine transformation) and PCA (Principal Component Analysis) is proposed.
Abstract: An innovative method to obtain 2-Dimensional images which are nearly lossless in compression using DCT (discrete cosine transformation) and PCA (Principal Component Analysis) is proposed. All the DCT transformed blocks are individually quantized, then an algorithm called Inverse of DCT is applied on those quantized values, produced miscalculations in the remaining code is sequenced. The expansion of logical and mechanical requests of high-goal sight and sound content has incredibly expanded the information volume in big business server farms and workers on the internet. Our half and half methodology take advantage of (I) PCA to diminish the dimensionality of the picture, and (ii) DTT calculation to improve the picture quality The parameters of these processes are set employing compression with the help of metrics which is based on performance. A different process is performed on the values that accomplish the relationship between DCT values with high energy. The result goes under further entropy coding and gets compressed and gives a result that has a near-lossless standard of JPEG images.PCA is an arithmetical scheme that uses orthogonal conversions to turn a hypothetically interrelated set of records into a linearly uncorrelated set of data that contain principal value components. The PCA will be under and same as the total no. of available variables in the unique dataset. Furthermore, the PCs are arranged in such a way that the very first factor has the biggest possible alteration in the data, and every following component has the next highest variance.

1 citations

References
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Proceedings ArticleDOI
15 Apr 2013
TL;DR: Two algorithms based on DWT are proposed, these are, pixel averaging & maximum pixel replacement approach, which provide better results for image fusion.
Abstract: Image Fusion is a process of combining the relevant information from a set of images, into a single image, wherein the resultant fused image will be more informative and complete than any of the input images. This paper discusses the Formulation, Process Flow Diagrams and algorithms of PCA (principal Component Analysis), DCT (Discrete Cosine Transform) and DWT (Discrete Wavelet Transform) based image fusion techniques. The results are also presented in table & picture format for comparative analysis of above techniques. The PCA & DCT are conventional fusion techniques with many drawbacks, whereas DWT based techniques are more favorable as they provides better results for image fusion. In this paper, two algorithms based on DWT are proposed, these are, pixel averaging & maximum pixel replacement approach.

83 citations

Proceedings ArticleDOI
22 Mar 2013
TL;DR: The results show the proposed algorithm has a better visual quality than the base methods and the quality of the fused image has been evaluated using a set of quality metrics.
Abstract: Image Fusion is the process of combining information of two or more images into a single image which can retain all important features of the all original images. Here the input to fusion involves set of images taken from different modalities of the same scene. Output is a better quality image; which depends on a particular application. The objective of fusion is to generate an image which describes a scene better or even higher than any single image with respect to some relevant properties providing an informative image. These fusion techniques are important in diagnosing and treating cancer in medical fields. This paper focuses on the development of an image fusion method using Dual Tree Complex Wavelet Transform. The results show the proposed algorithm has a better visual quality than the base methods. Also the quality of the fused image has been evaluated using a set of quality metrics.

44 citations

Proceedings ArticleDOI
25 Apr 2012
TL;DR: This paper illustrates different multimodality medical image fusion techniques and their results assessed with various quantitative metrics and inferred that Mamdani type MIN-SUM-MOM is more productive than RDWT and also the proposed fusion techniques provide more information compared to the input images as justified by all the metrics.
Abstract: Image fusion is basically a process where multiple images (more than one) are combined to form a single resultant fused image. This fused image is more productive as compared to its original input images. The fusion technique in medical images is useful for resourceful disease diagnosis purpose. This paper illustrates different multimodality medical image fusion techniques and their results assessed with various quantitative metrics. Firstly two registered images CT (anatomical information) and MRI-T2 (functional information) are taken as input. Then the fusion techniques are applied onto the input images such as Mamdani type minimum-sum-mean of maximum (MIN-SUM-MOM) and Redundancy Discrete Wavelet Transform (RDWT) and the resultant fused image is analyzed with quantitative metrics namely Over all Cross Entropy(OCE), Peak Signal -to- Noise Ratio (PSNR), Signal to Noise Ratio (SNR), Structural Similarity Index(SSIM), Mutual Information(MI). From the derived results it is inferred that Mamdani type MIN-SUM-MOM is more productive than RDWT and also the proposed fusion techniques provide more information compared to the input images as justified by all the metrics.

32 citations


"VLSI Implementation of Discrete Cos..." refers background in this paper

  • ...Prakash, C et al.[4], has mentioned as image fusion is a basic route in which various images are combined as one resulted fused image which consists of higher information than input image and useful in medical images for diagnosing diseases....

    [...]

Proceedings ArticleDOI
21 Mar 2012
TL;DR: Evaluation by objective technical quality of medical images fused is feasible and successful and proves that the fusion with RATIO and contrast techniques to offer the best results.
Abstract: The quality of the medical image can be evaluated by several subjective techniques. However, the objective technical assessments of the quality of medical imaging have been recently proposed. The fusion of information from different imaging modalities allows a more accurate analysis. We have developed new techniques based on the multiresolution fusion. MRI and PET images have been fused with eight multi resolution techniques. For the evaluation of fusion images obtained, we opted by objective techniques. The results p rove that the fusion with RATIO and contrast techniques to offer the best results. Evaluation by objective technical quality of medical i mages fused is feasible and successful.

16 citations

Journal ArticleDOI
TL;DR: The proposed architecture is exploited to design two families of architectures for the 2D-DCT, namely, folded and full-parallel, with relevant complexity saving compared with the state-of-the-art implementations.
Abstract: This paper proposes an area-efficient fixed-point architecture for the computation of the discrete cosine transform (DCT) of multiple sizes in high efficiency video coding (HEVC). This result is obtained by comparing different DCT factorizations in order to find the most suitable one for implementation in the HEVC encoder. The recursive structure of fast algorithms, which decompose the $N$ -point DCT by means of two $N/2$ -point DCTs, is exploited to execute computations of small-size DCTs in parallel, thus maximizing the hardware re-usability while maintaining a constant throughput. The simulation results prove that the proposed solution features reduced rate-distortion loss es, with relevant complexity saving compared with the state-of-the-art implementations. Finally, the proposed architecture is exploited to design two families of architectures for the 2D-DCT, namely, folded and full-parallel.

16 citations


"VLSI Implementation of Discrete Cos..." refers methods in this paper

  • ...Maurizio Masera etal[10], exploited folded and full parallel 2D DCT architectures and the from simulation results proposed design is having less distortion losses with low complexity....

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