image compression ratio

2011 ◽  
Keyword(s):  
Image Compression ◽  
Compression Ratio

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 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.

What Is Wrong with Compression Ratio in Lossy Image Compression?

Radiology ◽  
2007 ◽  
Vol 245 (1) ◽  
pp. 299-300 ◽  
Author(s):  
Aleš Fidler ◽  
Boštjan Likar
Keyword(s):  
Image Compression ◽  
Compression Ratio

Image Compression Algorithm with Radix-4 FFT

2010 ◽  
Vol 143-144 ◽  
pp. 404-408
Author(s):  
Jia Bin Deng ◽  
Juan Li Hu ◽  
He Hua Chi ◽  
Jue Bo Wu
Keyword(s):  
Image Processing ◽  
Fourier Transform ◽  
Image Compression ◽  
Compression Ratio ◽  
Conformal Symmetry ◽  
Research Focus ◽  
Data Store ◽  
Long Time ◽  
Image Compression Algorithm

Image compression technology has been the research focus in the field of image processing all the time. In this paper, Radix-4 FFT is introduced to realize limit distortion coding of image. The presented method aims to solve the problems of Fourier transform on existing complexity and long time-consuming, and it can reduce the number of data store by conformal symmetry of Fourier transform. Using Radix-4 FFT, the time-consuming can be highly shortened and two different kinds of quantization tables are designed according to image compression ratio and the quality of image.

scholarly journals Image Compression Based on Arithmetic Coding Algorithm

2021 ◽  
pp. 329-334
Author(s):  
Ruaa Ibrahim Yousif ◽  
Nassir Hussein Salman
Keyword(s):  
Image Quality ◽  
Image Compression ◽  
Compression Ratio ◽  
Rapid Development ◽  
Arithmetic Coding ◽  
Compact Form ◽  
Color Model ◽  
Cosine Transform ◽  
High Image Quality ◽  
The Past

The past years have seen a rapid development in the area of image compression techniques, mainly due to the need of fast and efficient techniques for storage and transmission of data among individuals. Compression is the process of representing the data in a compact form rather than in its original or incompact form. In this paper, integer implementation of Arithmetic Coding (AC) and Discreet Cosine Transform (DCT) were applied to colored images. The DCT was applied using the YCbCr color model. The transformed image was then quantized with the standard quantization tables for luminance and chrominance. The quantized coefficients were scanned by zigzag scan and the output was encoded using AC. The results showed a decent compression ratio with high image quality.

scholarly journals DESIGN OF NEURAL NETWORK AS DATA FLOW MODEL FOR IMAGE COMPRESSION

2013 ◽  
pp. 195-199
Author(s):  
DANESHWARI I. HATTI ◽  
SAVITRI RAJU ◽  
MAHENDRA M. DIXIT
Keyword(s):  
Neural Network ◽  
Image Compression ◽  
Discrete Cosine Transform ◽  
Compression Ratio ◽  
Convergence Time ◽  
Training Algorithms ◽  
Hardware Complexity ◽  
Cosine Transform ◽  
Hidden Neurons

In digital communication bandwidth is essential parameter to be considered. Transmission and storage of images requires lot of memory in order to use bandwidth efficiently neural network and Discrete cosine transform together are used in this paper to compress images. Artificial neural network gives fixed compression ratio for any images results in fixed usage of memory and bandwidth. In this paper multi-layer feedforward neural network has been employed to achieve image compression. The proposed technique divides the original image in to several blocks and applies Discrete Cosine Transform (DCT) to these blocks as a pre-process technique. Quality of image is noticed with change in training algorithms, convergence time to attain desired mean square error. Compression ratio and PSNR in dB is calculated by varying hidden neurons. The proposed work is designed using MATLAB 7.10. and synthesized by mapping on Vertex 5 in Xilinx ISE for understanding hardware complexity. Keywords - backpropagation, Discrete

scholarly journals 375. Studies of image compression ratio by FCR optical disk filling system

1991 ◽  
Vol 47 (8) ◽  
pp. 1406
Author(s):  
H. Waki ◽  
A. Yamada ◽  
J. Kurumizawa ◽  
S. Komura ◽  
S. Hatakeyama ◽  
...  
Keyword(s):  
Image Compression ◽  
Compression Ratio ◽  
Optical Disk ◽  
Filling System
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