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.

A NONUNIFORM HIGH-QUALITY IMAGE COMPRESSION METHOD TO PRESERVE USER-SPECIFIED COMPRESSION RATIO

2011 ◽  
Vol 11 (03) ◽  
pp. 355-375 ◽  
Author(s):  
MOHAMMAD REZA BONYADI ◽  
MOHSEN EBRAHIMI MOGHADDAM
Keyword(s):  
Image Compression ◽  
Compression Ratio ◽  
Signal To Noise Ratio ◽  
Linear Mapping ◽  
Compression Method ◽  
High Quality ◽  
Compressed Images ◽  
High Quality Image ◽  
Quality Image

Most of image compression methods are based on frequency domain transforms that are followed by a quantization and rounding approach to discard some coefficients. It is obvious that the quality of compressed images highly depends on the manner of discarding these coefficients. However, finding a good balance between image quality and compression ratio is an important issue in such manners. In this paper, a new lossy compression method called linear mapping image compression (LMIC) is proposed to compress images with high quality while the user-specified compression ratio is satisfied. This method is based on discrete cosine transform (DCT) and an adaptive zonal mask. The proposed method divides image to equal size blocks and the structure of zonal mask for each block is determined independently by considering its gray-level distance (GLD). The experimental results showed that the presented method had higher pick signal to noise ratio (PSNR) in comparison with some related works in a specified compression ratio. In addition, the results were comparable with JPEG2000.

scholarly journals Backpropagation Neural Network Implementation for Medical Image Compression

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Kamil Dimililer
Keyword(s):  
Neural Network ◽  
Image Compression ◽  
Compression Ratio ◽  
Haar Wavelet ◽  
Compression Method ◽  
High Compression Ratio ◽  
Haar Wavelet Transform ◽  
X Ray ◽  
Ideal Image ◽  
And Storage

Medical images require compression, before transmission or storage, due to constrained bandwidth and storage capacity. An ideal image compression system must yield high-quality compressed image with high compression ratio. In this paper, Haar wavelet transform and discrete cosine transform are considered and a neural network is trained to relate the X-ray image contents to their ideal compression method and their optimum compression ratio.

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.

scholarly journals Survey of Hybrid Image Compression Techniques

2017 ◽  
Vol 7 (4) ◽  
pp. 2206
Author(s):  
Emy Setyaningsih ◽  
Agus Harjoko
Keyword(s):  
Image Compression ◽  
Compression Ratio ◽  
Lossless Compression ◽  
Quality Data ◽  
Compression Method ◽  
Compression Process ◽  
High Quality ◽  
Compression Technique ◽  
Technique Development

A compression process is to reduce or compress the size of data while maintaining the quality of information contained therein. This paper presents a survey of research papers discussing improvement of various hybrid compression techniques during the last decade. A hybrid compression technique is a technique combining excellent properties of each group of methods as is performed in JPEG compression method. This technique combines lossy and lossless compression method to obtain a high-quality compression ratio while maintaining the quality of the reconstructed image. Lossy compression technique produces a relatively high compression ratio, whereas lossless compression brings about high-quality data reconstruction as the data can later be decompressed with the same results as before the compression. Discussions of the knowledge of and issues about the ongoing hybrid compression technique development indicate the possibility of conducting further researches to improve the performance of image compression method.

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 PENILAIAN KUALITAS PEMAMPATAN CITRA PADA APLIKASI-APLIKASI INSTANT MESSENGER

2017 ◽  
Vol 10 (2) ◽  
pp. 78
Author(s):  
Khoiru Nurfitri ◽  
M. Suyanto ◽  
Sukoco .
Keyword(s):  
Image Compression ◽  
Compression Ratio ◽  
Comparative Research ◽  
Quality Index ◽  
Input Image ◽  
High Compression Ratio ◽  
Initial Image ◽  
Instant Messenger ◽  
Speed Up

Useful image compression to compress the file size of the image thus saving storage and speed up the transfer process. This study aims to measuring on the quality of the image as compressed by instant messenger application by comparing the initial image or the input image with the image compression results. The assessment is based on objective criteria by using research methods of comparative research. The objective criteria used is the compression ratio, PSNR, the quality index, and SSIM. From this research it is known that each - each instant messenger applications have a compression ratio that varies. In addition, PSNR, SSIM, and quality index are different too. From the analysis concluded that the order of the image that has a fairly high compression ratio and good quality is the Line

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.

Compression of Secondary Ion Microscopy Image Sets Using a Three-dimensional Wavelet Transformation

2000 ◽  
Vol 6 (1) ◽  
pp. 68-75 ◽  
Author(s):  
Martin G. Wolkenstein ◽  
Herbert Hutter
Keyword(s):  
Image Compression ◽  
Wavelet Transformation ◽  
Signal To Noise Ratio ◽  
Three Dimensional ◽  
Compression Method ◽  
Signal To Noise ◽  
Microscopy Image ◽  
Image Set ◽  
Ion Microscopy ◽  
Secondary Ion

This article proposes a lossy three-dimensional (3-D) image compression method for 3-D secondary ion microscopy (SIMS) image sets that uses a separable nonuniform 3-D wavelet transform. A typical 3-D SIMS measurement produces relatively large amounts of data which has to be reduced for archivation purposes. Although it is possible to compress an image set slice by slice, more efficient compression can be achieved by exploring the correlation between slices. Compared to different two-dimensional (2-D) image compression methods, compression ratios of the 3-D wavelet method are about four times higher at a comparable peak signal-to-noise ratio (PSNR).

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