Pipeline Architecture of Forward and Inverse Photo Core Transform for JPEG XR Image Compression

2021 ◽  
Author(s):  
Abhishek Baba ◽  
Rakesh Biswas
Keyword(s):  
Image Compression ◽  
Pipeline Architecture ◽  
Jpeg Xr

SMART SENSOR: AN ON-BOARD IMAGE PROCESSING SYSTEM FOR REAL-TIME REMOTE SENSING

2002 ◽  
Vol 02 (03) ◽  
pp. 481-499
Author(s):  
JANE YOU ◽  
DAVID ZHANG
Keyword(s):  
Remote Sensing ◽  
Image Analysis ◽  
Image Compression ◽  
Real Time ◽  
Processing System ◽  
Smart Sensor ◽  
Pipeline Architecture ◽  
New Approach ◽  
Hardware Processing ◽  
Sensor System Design

This paper presents a new approach to smart sensor system design for real-time remote sensing. A combination of techniques for image analysis and image compression is investigated. The proposed algorithms include: (1) a fractional discrimination function for image analysis, (2) a comparison of effective algorithms for image compression, (3) a pipeline architecture for parallel image classification and compression on-board satellites, and (4) a task control strategy for mapping image computing models to hardware processing elements. The efficiency and accuracy of the proposed techniques are demonstrated throughout system simulation.

scholarly journals Subjective evaluation of JPEG XR image compression

2009 ◽  
Author(s):  
Francesca De Simone ◽  
Lutz Goldmann ◽  
Vittorio Baroncini ◽  
Touradj Ebrahimi
Keyword(s):  
Image Compression ◽  
Subjective Evaluation ◽  
Jpeg Xr

Compression Method for Good Visual Quality Based on JPEG XR

2014 ◽  
Vol 926-930 ◽  
pp. 3384-3388
Author(s):  
Hua Jie Cai ◽  
Xin Tian ◽  
Tao Li
Keyword(s):  
Image Compression ◽  
Visual Quality ◽  
Structural Similarity ◽  
Image Feature ◽  
Compression Method ◽  
Compression Performance ◽  
Jpeg Xr ◽  
Future Work ◽  
The Relationship ◽  
Activity Measure

A compression method for good visual quality is proposed in this paper. It is based on JPEG-XR. The visual quality is measured by structural similarity (SSIM). By some image compression experiments, the minimum SSIM is determined in a manual way. It represents the required visual quality. The image activity measure (IAM) is selected as an image feature. The relationship between IAM and image compression performance under different quantization parameters (QPs) is analyzed. Based on this relationship, proper QPs can be chosen for different images. Then JPEG XR can be used to compress images with these QPs, which will result in good visual quality with fewer bits consumed. The experiments have verified the effectiveness of the proposed method. How to choose a suitable image feature may be our future work.

Image Compression Using Vector Quantization with Variable Block Size Division

2010 ◽  
Vol 130 (8) ◽  
pp. 1431-1439 ◽  
Author(s):  
Hiroki Matsumoto ◽  
Fumito Kichikawa ◽  
Kazuya Sasazaki ◽  
Junji Maeda ◽  
Yukinori Suzuki
Keyword(s):  
Image Compression ◽  
Vector Quantization ◽  
Block Size ◽  
Variable Block
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