Textual image compression at low bit rates based on region-of-interest coding

Grailu, Hadi

doi:10.1007/s10032-015-0258-7

Cited by 3 publications

(6 citation statements)

References 20 publications

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“…Finally, the compression of the segmented blocks was made by the arithmetic coder, Huffman coder and JPEG coder. The effectiveness of the proposed segmentation technique is higher than the existing method, which can be examined by the contrast between the segmentation results of proposed KCOA method with the existing K-means algorithm, fuzzy C-means algorithms and using [16,17]. Moreover, the compression ratio and the image quality assessment measures were computed and the efficiency of the projected method can be evaluated by the compressed image and the segmented image.…”

Section: Resultsmentioning

confidence: 99%

“…Grailu [17] have explained that the set partitioning in hierarchical trees coder which was used in the framework of ROI coding along with some image enhancement techniques. So as to remove the leakage effect, the process may take place in the wavelet-based low-bit-rate compression.…”

Section: Related Workmentioning

confidence: 99%

“…Additionally, the efficiency of the proposed compression strategy is examined and contrasted by the existing methods. Also, the compression ratio values are obtained for text, image and background which are segmented by K-means, FCM, using [16], using [17] and proposed K-means cuckoo algorithm for the test images (1)(2)(3)(4)(5). These are specified in Table 2.…”

Section: Performance Evaluation For Compound Image Compressionmentioning

confidence: 99%

“…Moreover, it is clearly seen that better compression ratio is attained for the proposed technique when compared with the existing ones. Table 3 shows the performance evaluation in terms of PSNR and structural similarity (SSIM) obtained for the test images (1-5) for the techniques such as KCOA, FCM, using [16], using [17] and K-means algorithms.…”

Section: Performance Evaluation For Compound Image Compressionmentioning

confidence: 99%

See 3 more Smart Citations

AC coefficient and K‐means cuckoo optimisation algorithm‐based segmentation and compression of compound images

Manju

Fred²

2018

IET Image Processing

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Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Performance Evaluation For Compound Image Compressionmentioning

confidence: 99%

Section: Performance Evaluation For Compound Image Compressionmentioning

confidence: 99%

See 2 more Smart Citations

AC coefficient and K‐means cuckoo optimisation algorithm‐based segmentation and compression of compound images

Manju

Fred²

2018

IET Image Processing

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“…The ROI based lossless image compression with Embedded Zero-tree Wavelet (EZW) Algorithm [9] is designed for better diagnosis and compared with other techniques like Haar Wavelet (HW) [10] and Daubechies wavelet (DbW) Transformation with better image quality. The Burrows-Wheeler (BW) Transform and Move to Front(MTF) transform with Huffman encoding and hybrid fractal encoding [11] and DWT followed by SPHIT technique [12] are ROI based hybrid compression approach applicable to medical MRI images with CR improvements. The ROI of radiological Image applied to Vedic compression algorithm [13] on software approach with improvement in computation speed, compression ratio and visual quality outcomes with different image database over conventional DCT approach.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Design Approach of ROI Based DWT Using Vedic and Wallace Tree Multiplier on FPGA Platform

Sm¹,

Suresh²

2019

IJECE

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<span lang="EN-US">In digital image processing, the compression mechanism is utilized to enhance the visual perception and storage cost. By using hardware architectures, reconstruction of medical images especially Region of interest (ROI) part using Lossy image compression is a challenging task. In this paper, the ROI Based Discrete wavelet transformation (DWT) using separate Wallace- tree multiplier (WM) and modified Vedic Multiplier (VM) methods are designed. The Lifting based DWT method is used for the ROI compression and reconstruction. The 9/7 filter coefficients are multiplied in DWT using Wallace- tree multiplier (WM) and modified Vedic Multiplier (VM). The designed Wallace tree multiplier works with the parallel mechanism using pipeline architecture results with optimized hardware resources, and 8x8 Vedic multiplier designs improves the ROI reconstruction image quality and fast computation. To evaluate the performance metrics between ROI Based DWT-WM and DWT-VM on FPGA platform, The PSNR and MSE are calculated for different Brain MRI images, and also hardware constraints include Area, Delay, maximum operating frequency and power results are tabulated. The proposed model is designed using Xilinx platform using Verilog-HDL and simulated using ModelSim and Implemented on Artix-7 FPGA device.</span>

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Sparse Decomposition Technique for Segmentation and Compression of Compound Images

Manju

Fred²

2018

Journal of Intelligent Systems

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AbstractCompression of compound records and images can be more cumbersome than the original information since they can be a mix of text, picture and graphics. The principle requirement of the compound record or images is the nature of the compressed data. In this paper, diverse procedures are used under block-based classification to distinguish the compound image segments. The segmentation process starts with separation of the entire image into blocks by spare decomposition technique in smooth blocks and non smooth blocks. Gray wolf-optimization based FCM (fuzzy C-means) algorithm is employed to segment background, text, graphics, images and overlap, which are then individually compressed using adaptive Huffman coding, embedded zero wavelet and H.264 coding techniques. Exploratory outcomes demonstrate that the proposed conspire expands compression ratio, enhances image quality and additionally limits computational complexity. The proposed method is implemented on the working platform of MATLAB.

show abstract

Textual image compression at low bit rates based on region-of-interest coding

Cited by 3 publications

References 20 publications

AC coefficient and K‐means cuckoo optimisation algorithm‐based segmentation and compression of compound images

AC coefficient and K‐means cuckoo optimisation algorithm‐based segmentation and compression of compound images

An Efficient Design Approach of ROI Based DWT Using Vedic and Wallace Tree Multiplier on FPGA Platform

Sparse Decomposition Technique for Segmentation and Compression of Compound Images

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