Image Compression Technique for Low Bit Rate Transmission

2011 ◽  
Vol 1 (4) ◽  
pp. 1-18
Author(s):  
Shaimaa A. El-said ◽  
Khalid F. A. Hussein ◽  
Mohamed M. Fouad
Keyword(s):  
Image Compression ◽  
Compression Ratio ◽  
Signal To Noise Ratio ◽  
Bit Rate ◽  
High Compression Ratio ◽  
Compression Technique ◽  
Low Bit Rate ◽  
High Compression ◽  
Rate Transmission ◽  
Visual Degradation

A novel Adaptive Lossy Image Compression (ALIC) technique is proposed to achieve high compression ratio by reducing the number of source symbols through the application of an efficient technique. The proposed algorithm is based on processing the discrete cosine transform (DCT) of the image to extract the highest energy coefficients in addition to applying one of the novel quantization schemes proposed in the present work. This method is straightforward and simple. It does not need complicated calculation; therefore the hardware implementation is easy to attach. Experimental comparisons are carried out to compare the performance of the proposed technique with those of other standard techniques such as the JPEG. The experimental results show that the proposed compression technique achieves high compression ratio with higher peak signal to noise ratio than that of JPEG at low bit rate without the visual degradation that appears in case of JPEG.

Image Compression Technique for Low Bit Rate Transmission

2013 ◽  
pp. 1306-1322
Author(s):  
Shaimaa A. El-said ◽  
Khalid F. A. Hussein ◽  
Mohamed M. Fouad
Keyword(s):  
Image Compression ◽  
Compression Ratio ◽  
Signal To Noise Ratio ◽  
Bit Rate ◽  
High Compression Ratio ◽  
Compression Technique ◽  
Low Bit Rate ◽  
High Compression ◽  
Rate Transmission ◽  
Visual Degradation

A novel Adaptive Lossy Image Compression (ALIC) technique is proposed to achieve high compression ratio by reducing the number of source symbols through the application of an efficient technique. The proposed algorithm is based on processing the discrete cosine transform (DCT) of the image to extract the highest energy coefficients in addition to applying one of the novel quantization schemes proposed in the present work. This method is straightforward and simple. It does not need complicated calculation; therefore the hardware implementation is easy to attach. Experimental comparisons are carried out to compare the performance of the proposed technique with those of other standard techniques such as the JPEG. The experimental results show that the proposed compression technique achieves high compression ratio with higher peak signal to noise ratio than that of JPEG at low bit rate without the visual degradation that appears in case of JPEG.

Image Compression Technique for Low Bit Rate Transmission

2013 ◽  
pp. 211-229
Author(s):  
Shaimaa A. El-said ◽  
Khalid F. A. Hussein ◽  
Mohamed M. Fouad
Keyword(s):  
Image Compression ◽  
Compression Ratio ◽  
Signal To Noise Ratio ◽  
Bit Rate ◽  
High Compression Ratio ◽  
Compression Technique ◽  
Low Bit Rate ◽  
High Compression ◽  
Rate Transmission ◽  
Visual Degradation

A novel Adaptive Lossy Image Compression (ALIC) technique is proposed to achieve high compression ratio by reducing the number of source symbols through the application of an efficient technique. The proposed algorithm is based on processing the discrete cosine transform (DCT) of the image to extract the highest energy coefficients in addition to applying one of the novel quantization schemes proposed in the present work. This method is straightforward and simple. It does not need complicated calculation; therefore the hardware implementation is easy to attach. Experimental comparisons are carried out to compare the performance of the proposed technique with those of other standard techniques such as the JPEG. The experimental results show that the proposed compression technique achieves high compression ratio with higher peak signal to noise ratio than that of JPEG at low bit rate without the visual degradation that appears in case of JPEG.

scholarly journals Design and Development of a Very Large Scale Integrated Circuit Architecture for a Digital Image Compression and Realization on Field Programmable Gate Array

2020 ◽  
Vol 9 (3) ◽  
pp. 3510-3516
Keyword(s):  
Image Compression ◽  
Compression Ratio ◽  
Integrated Circuit ◽  
Large Scale ◽  
Image Data ◽  
High Compression Ratio ◽  
Compression Technique ◽  
Research Challenges ◽  
High Compression ◽  
Image Pixels

The domain of image signal processing, image compression is the significant technique, which is mainly invented to reduce the redundancy of image data in order to able to transmit the image pixels with high quality resolution. The standard image compression techniques like losseless and lossy compression technique generates high compression ratio image with efficient storage and transmission requirement respectively. There are many image compression technique are available for example JPEG, DWT and DCT based compression algorithms which provides effective results in terms of high compression ratio with clear quality image transformation. But they have more computational complexities in terms of processing, encoding, energy consumption and hardware design. Thus, bringing out these challenges, the proposed paper considers the most prominent research papers and discuses FPGA architecture design and future scope in the state of art of image compression technique. The primary aim to investigate the research challenges toward VLSI designing and image compression. The core section of the proposed study includes three folds viz standard architecture designs, related work and open research challenges in the domain of image compression.

IMPROVED IMAGE COMPRESSION BASED ON FEED-FORWARD ADAPTIVE DOWNSAMPLING ALGORITHM

2009 ◽  
Vol 09 (04) ◽  
pp. 575-589 ◽  
Author(s):  
SATISH KUMAR SINGH ◽  
SHISHIR KUMAR
Keyword(s):  
Image Compression ◽  
Compression Ratio ◽  
Mathematical Formulation ◽  
Video Data ◽  
Visual Signals ◽  
Bit Rate ◽  
High Compression Ratio ◽  
Mathematical Basis ◽  
Feed Forward ◽  
High Compression

All the visual signals used in internet, mobile and multimedia applications are needed to be coded at very low bit rates, without affecting much the quality of image or video data. To achieve a very low bit rate and very high compression ratio the image can be downsampled prior to compression and the full resolution image can be obtained by estimating the missing portion after decompression with reward of better PSNR. In this paper an attempt has been made to design an improved image compression system based on the feed forward adaptive downsampling algorithm considering the visual significance of the image. The mathematical basis has been established for visual significance and downsampling parameters, the mathematical formulation has also been established to get the PSNR value reconstructed image, without the actual reconstruction on the downsampled image in terms of known pixel values, remained after downsampling. Through this paper a fast image compression method is proposed which is having high compression ratio, feed-forward nature, acceptable signal-to-noise ratio and is application oriented. This method can also be used further for variable bit rate application.

scholarly journals 3D DCT Based Image Compression Method for the Medical Endoscopic Application

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1817
Author(s):  
Jiawen Xue ◽  
Li Yin ◽  
Zehua Lan ◽  
Mingzhu Long ◽  
Guolin Li ◽  
...  
Keyword(s):  
Image Compression ◽  
Compression Ratio ◽  
Signal To Noise Ratio ◽  
Blocking Artifacts ◽  
Compression Method ◽  
High Compression Ratio ◽  
Multiplication Operation ◽  
3D Data ◽  
Wireless Capsule

This paper proposes a novel 3D discrete cosine transform (DCT) based image compression method for medical endoscopic applications. Due to the high correlation among color components of wireless capsule endoscopy (WCE) images, the original 2D Bayer data pattern is reconstructed into a new 3D data pattern, and 3D DCT is adopted to compress the 3D data for high compression ratio and high quality. For the low computational complexity of 3D-DCT, an optimized 4-point DCT butterfly structure without multiplication operation is proposed. Due to the unique characteristics of the 3D data pattern, the quantization and zigzag scan are ameliorated. To further improve the visual quality of decompressed images, a frequency-domain filter is proposed to eliminate the blocking artifacts adaptively. Experiments show that our method attains an average compression ratio (CR) of 22.94:1 with the peak signal to noise ratio (PSNR) of 40.73 dB, which outperforms state-of-the-art methods.

scholarly journals Modified Block Compressed Sensing for Extraction of Fetal Electrocardiogram from Mother Electrocardiogram Using Block Compressed Sensing Based Guided FOCUSS and FAST-Independent Component

2021 ◽  
Vol 50 (1) ◽  
pp. 123-137
Author(s):  
Muhammad Tayyib Awan ◽  
Muhammad Amir ◽  
Sarmad Maqsood ◽  
Musyyab Yousufi ◽  
Suheel Abdullah ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Compression Ratio ◽  
Ecg Signal ◽  
High Compression Ratio ◽  
Sensing Matrix ◽  
Compression Technique ◽  
High Compression ◽  
Fetal Ecg ◽  
Block Compressed Sensing ◽  
Modified Block

Fetal ECG extraction from abdominal ECG is critical task for telemonitoring of fetus which require lot of understanding to the subject. Conventional source separation methods are not efficient enough to separate FECG from huge multichannel ECG. Thus use of compression technique is needed to compress and reconstruct ECG signal without any significant losses in quality of signal. Compressed sensing shows promising results for such tasks. However, current compressed sensing theory is not so far that successful due to the non-sparsity and strong noise contamination present in ECG signal. The proposed work explores the concept of block compressed sensing to reconstruct non-sparse FECG signal using GFOCUSS algorithm. The main objective of this paper is not only to successfully reconstruct the ECG signal but to efficiently separate FECG from abdominal ECG. The proposed algorithm is explained in very extensive manner for all experiments. The key feature of proposed method is, that it doesn’t affect the interdependence relation between multichannel ECG. The useof walsh sensing matrix made it possible to achieve high compression ratio. Experimental results shows that even at very high compression ratio, successful FECG reconstruction from raw ECG is possible. These results are validated using PSNR, SINR, and MSE. This shows the framework, compared to other algorithms such as current blocking CS algorithms, rackness CS algorithm and wavelet algorithms, can greatly reduce code execution time during data compression stage and achieve better reconstruction in terms of MSE, PSNR and SINR.

scholarly journals Investigating the Effect of Block Length on the Performance of Fractal Coding Using Audio Files

2020 ◽  
Author(s):  
Ahmed Hussain Ali ◽  
Loay Edwar George ◽  
Omar S. Saleh ◽  
Mohd Rosmadi Mokhtar ◽  
Qusay Al-Maatouk
Keyword(s):  
Compression Ratio ◽  
Audio Signal ◽  
Block Length ◽  
High Compression Ratio ◽  
Compression Technique ◽  
Fractal Coding ◽  
Audio Quality ◽  
High Compression ◽  
Audio Data ◽  
Audio Files

The goal of compression techniques is to reducing the size of data and decreasing the communication cost while transferring data. Fractal based coding technique is widely used to compress images files which provides high compression ratio and good image quality. However, like a compression technique, it is still limited because of the difference of the human perceptions between audio and image files, the long time for searching the best possible domain blocks and many comparisons in the encoding process. For those reasons, Fractal Coding had not broadly studied on audio data. Few years ago, Fractal Coding has been extended to apply on the audio data. In this paper, the application of the Fractal Coding on different types of audio files is investigated. Moreover, the effect of block length on the audio quality and compression performance are highlighted since block length is considered the main factor in the Fractal Coding algorithm. A GTZAN dataset is adopted in the evaluation and the experimental results show that there is an inverse relationship between block length and audio quality and proportional relationship between block length and compression ratio and factor. Furthermore, it can be noticed that the Fractal Coding can be compressed any speech and music audio signal directly with acceptable quality, PSNR 39 dB on average with a high compression ratio around 90 % with compression factor around 10 when the block length is 20 samples.

An Efficient Lossless Medical Image Compression Using Hybrid Algorithm

2014 ◽  
Vol 984-985 ◽  
pp. 1276-1281
Author(s):  
C. Priya ◽  
T. Kesavamurthy ◽  
M. Uma Priya
Keyword(s):  
Image Compression ◽  
Compression Ratio ◽  
Performance Metrics ◽  
Signal To Noise Ratio ◽  
Set Partitioning ◽  
Compression Technique ◽  
Computational Speed ◽  
Reconstruction Quality ◽  
Spiht Algorithm ◽  
Pyramid Structures

Recently many new algorithms for image compression based on wavelets have been developed.This paper gives a detailed explanation of SPIHT algorithm with the combination of Lempel Ziv Welch compression technique for image compression by MATLAB implementation. Set partitioning in Hierarchical trees (SPIHT) is one of the most efficient algorithm known today. Pyramid structures have been created by the SPIHT algorithm based on a wavelet decomposition of an image. Lempel Ziv Welch is a universal lossless data compression algorithm guarantees that the original information can be exactly reproduced from the compressed data.The proposed methods have better compression ratio, computational speed and good reconstruction quality of the image. To analysis the proposed lossless methods here, calculate the performance metrics as Compression ratio, Mean square error, Peak signal to Noise ratio. Key Words-LempelZivWelch (LZW),SPIHT,Wavelet

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