Papers by Dr. NAVEEN KUMAR R
—The most significant parameters of image processing are image resolution and speed of processing... more —The most significant parameters of image processing are image resolution and speed of processing. Compressing the multimedia datasets, which are rich in quality and volume is challenging. Wavelet based image compression techniques are the best tools for lossless image compression, however, they suffer by low compression ratio. Conversely fractional cosine transform based compression is a lossy compression technique with less image quality. In this paper, an improved compression technique is proposed by using wavelet transform and discrete fractional cosine transform to achieve high quality of reconstruction of an image at high compression rate. The algorithm uses wavelet transform to decompose image into frequency spectrum with low and high frequency sub bands. Application of quantization process for both sub bands at two levels increases the number of zeroes, however rich zeroes from high frequency sub bands are eliminated by creating the blocks and then storing only non-zero values and kill all blocks with zero values to form reduced array. The arithmetic coding method is used to encode the sub bands. The Experimental results of proposed method are compared with its primitive two dimensional fractional cosine and fractional Fourier compression algorithms and some significant improvements can be observed in peak signal to noise ratio and self-similarity index mode at high compression ratio.
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Today's smart world with high-speed communication devices demands elegant computing systems with ... more Today's smart world with high-speed communication devices demands elegant computing systems with lightening speed. Compression technology takes a major part in developing new generation computing systems. Popular applications like multimedia and medical data processing technology desires high data transmission rate, good perceptual signal quality and high compression rates. Wavelet based data compression techniques have advantages in lossless signal reconstructions and fit in dedicated data processing field. This paper highlights some wavelet transform based compression algorithms implementation and measuring performance towards quality of reconstruction and compression rate of one and two dimensional signal.
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Reducing the transmission cost while maintaining the quality of image data is the most
challengin... more Reducing the transmission cost while maintaining the quality of image data is the most
challenging part in data transmission. In this paper, we report the possibility of improving the quality
of image reconstruction by using modified singular value decomposition (SVD) and binary tree coding
with adaptive scanning order (BTCA) for grayscale image compression. This method uses modified
rank one updated SVD as a pre-processing step for binary tree coding to increase the quality of the
reconstructed image. The high energy compaction in SVD process offers high image quality with
less compression and is requires more number of bits for reconstruction. BTCA compression, also
gives high image quality by coding more significant coefficients using adaptive scanning order from
bottom to top with high compression rate. The proposed method uses both SVD and BTC for image
compression and is tested with several test images and results are compared with those of SPIHT,
JPEG, JPEG2000 and BTCA. The results show significant improvement in PSNR at high bitrates as
compared to other methods.
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Objectives: Image communication in web applications becomes handy because of highly developed com... more Objectives: Image communication in web applications becomes handy because of highly developed compression tools. Human eye fixate on an image's preview, carefully adjusting the quality and optimization settings until we've found that sweet spot, where the file size and quality are both the best they can possibly be. Method: This paper presents a new algorithm, which uses modified singular value decomposition (SVD) and adaptive Set Partition Hierarchical Tree (ASPIHT) for grayscale image compression. This hybrid method uses modified rank one updated SVD as a pre-processing step for ASPIHT to increase the quality of the reconstructed image. Findings: The high energy compaction in SVD process offers high image quality with less compression and requires a number of bits for reconstruction. On the other hand, ASPIHT compression also offers high image quality by coding more significant coefficients adaptively with high compression at specified bitrates. The proposed method is a combination of both SVD and ASPIHT for image compression and is tested with several test images and results are compared with those of SPIHT, ASPIHT without arithmetic coding and JPEG2000. Novelty: This method improves the quality of reconstruction without altering the compression rates of SPIHT algorithm. The tabulated results show significant improvement in PSNR at higher compression ratios as compared to other methods.
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The speedy budding signal processing technology in telemedicine field made physician trouble-free... more The speedy budding signal processing technology in telemedicine field made physician trouble-free in diagnosing the disease. But these advanced medical facilities, still unreachable in some remote areas because the lack of equipments, low bandwidth signals transmission and remote locations. Hence compression technology struggling to solve the problem of transmission rate by reducing the size of data without affecting the signal qualities. The wavelet based compression techniques are well suited for these type applications because of coding flexibility and multiresolution property. This paper presents qualitative analysis of wavelet based compression technique using some telemedicine samples ECG signal and MRI images. The quality of signal is measured by using PSNR.
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Rapid progress in mobile communication, demands high-speed multimedia data processing. This has l... more Rapid progress in mobile communication, demands high-speed multimedia data processing. This has lead the compression technology to speed up the process by reducing the size of data without disturbing image quality. This paper attempts to develop the quality of compression by using improved neigh shrink in hybrid wavelet algorithm to compress an image. After wavelet decomposition, one-dimensional Discrete Cosine Transform is applied to decorrelate approximate coefficients and stored as T-matrix. The detail coefficients are thresholded using 'improved neigh shrink' and Eliminate Zero and Store Data algorithm are applied to eliminate redundancy and stored as reduced array. The compressed approximate and detailed coefficients are encoded by arithmetic coding. The simulated results show that proposed algorithm has significant improvement in image quality in terms of PSNR and SSIM when compared with existed wavelet-based compression methods including JPEG 2000 at high compression rate.
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The study of image processing in the multimedia application becomes the very crucial part when it... more The study of image processing in the multimedia application becomes the very crucial part when its spectrum varying unpredictably. Processing of these images is a challenging part of computer technology; hence we are using Fourier transform to analyse the signal. But this transform is very general and failed to operate in critical conditions because of its less compactness. In this paper, a discrete fractional Fourier transform is studied as a compressing algorithm for different signals. One dimensional signal is used to evaluate the characterization of discrete fractional Fourier transform and measuring the performance of compression. Some comparisons are carried out with existing algorithms by measuring the PSNR and MSE. The simulation studies and comparison show some significant improvement in compression.
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Wavelet based image coding of JPEG2000's core coding system defined in part one provides a room t... more Wavelet based image coding of JPEG2000's core coding system defined in part one provides a room to improve a performance of image compression. But the development of hybrid Wavelet algorithms in last few years indicates their performance is far better than Wavelet method. This paper introduces new hybrid compression algorithm using Walsh wavelet transforms with variable wavelet threshold. Wavelet decomposition splits an image into low-frequency and high-frequency sub-bands. Application of 2D Walsh transform to low-frequency subband gives DC values and multi-array matrix. At the same time, high-frequency sub-bands at level one are ignored and level two sub-bands are compressed by wavelet threshold and quantization. Encode both the sub-bands by arithmetic code. Compression performance is analyzed by calculating PSNR and Compressed size with different quantization Factors for two grayscale images.
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Papers by Dr. NAVEEN KUMAR R
challenging part in data transmission. In this paper, we report the possibility of improving the quality
of image reconstruction by using modified singular value decomposition (SVD) and binary tree coding
with adaptive scanning order (BTCA) for grayscale image compression. This method uses modified
rank one updated SVD as a pre-processing step for binary tree coding to increase the quality of the
reconstructed image. The high energy compaction in SVD process offers high image quality with
less compression and is requires more number of bits for reconstruction. BTCA compression, also
gives high image quality by coding more significant coefficients using adaptive scanning order from
bottom to top with high compression rate. The proposed method uses both SVD and BTC for image
compression and is tested with several test images and results are compared with those of SPIHT,
JPEG, JPEG2000 and BTCA. The results show significant improvement in PSNR at high bitrates as
compared to other methods.
challenging part in data transmission. In this paper, we report the possibility of improving the quality
of image reconstruction by using modified singular value decomposition (SVD) and binary tree coding
with adaptive scanning order (BTCA) for grayscale image compression. This method uses modified
rank one updated SVD as a pre-processing step for binary tree coding to increase the quality of the
reconstructed image. The high energy compaction in SVD process offers high image quality with
less compression and is requires more number of bits for reconstruction. BTCA compression, also
gives high image quality by coding more significant coefficients using adaptive scanning order from
bottom to top with high compression rate. The proposed method uses both SVD and BTC for image
compression and is tested with several test images and results are compared with those of SPIHT,
JPEG, JPEG2000 and BTCA. The results show significant improvement in PSNR at high bitrates as
compared to other methods.