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Ezhilarasan, K.
- Performance Analysis of Image Compression Based on Fast Fractional Wavelet Transform Combined with Spiht for Medical Images
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Authors
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1 Department of Electronics and Communication Engineering, Sambhram Institute of Technology, IN
2 Department of Electronics and Instrumentation Engineering, JSS Academy of Technical Education, Bengaluru, IN
3 Department of Electronics and Communication Engineering, Dayananda Sagar University, IN
1 Department of Electronics and Communication Engineering, Sambhram Institute of Technology, IN
2 Department of Electronics and Instrumentation Engineering, JSS Academy of Technical Education, Bengaluru, IN
3 Department of Electronics and Communication Engineering, Dayananda Sagar University, IN
Source
ICTACT Journal on Image and Video Processing, Vol 8, No 3 (2018), Pagination: 1722-1729Abstract
Fast Fractional Wavelet Transform (FFWT) is an orthogonal linear transform called as decomposed signals in terms of chirps transform. This transform is used for signal and image compression and is based on Eigen value decomposition. In this paper, the performance analysis of image compression techniques based on the FFWT was discussed. FFWT is combined with the Set Partitioning in Hierarchical Tree (SPIHT) to achieve better compression ratio and biorthogonal filter banks for the analysis of compression performance with respect to subjective quality metrics. Further, the proposed work is compared with the various subject quantity parameters like PSNR and MSE.Keywords
Signal Compression, FFWT, SPIHT, Compression Ratio and Multiresolution Analysis.References
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- Digital Imaging of Objects behind Steel Walls using Drone
Abstract Views :91 |
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Authors
Affiliations
1 Department of Electronics and Communication Engineering, Sambhram Institute of Technology, Bengaluru, IN
1 Department of Electronics and Communication Engineering, Sambhram Institute of Technology, Bengaluru, IN
Source
Digital Image Processing, Vol 13, No 4 (2021), Pagination: 71-76Abstract
In this paper, we describe an innovative idea for digitally imaging objects behind steel involving the efficient utilization of Hexacopter (UAVs) to facilitate real-time structural health observation and analysis. Steel is an extensively utilized alloy for the manufacturing of enginery in most factories, manufacturing facilities, and industrial units. The subsistence and upkeep of these engineries might become very costly, tedious, and unproductive if it needs disassembling, close scrutiny, and then the reconstruction. Hence an attempt is made in discussing a creative approach that will facilitate enginery examination without disassembling of enginery just as imaging the human body through x-rays. This will aid to recognize the source of the fault in enginery and required measures can be taken., Most often heat is a preliminary indication of machinery damage or breakdown, making it important to observe and analyze, hence in preventive maintenance programs, use of radio, WiFi, heat, light, and sound signals via a drone for quick data accumulation from hazardous locations to get a digital image of the area being scanned from a safe distance from moving or energized types of equipment. Moreover, the current applications and future potential of drones in the industrial fields are discussed.Keywords
UAV (Unmanned Aerial Vehicle), Drone, Steel, XRay, Thermal Sensor, Image Processing Algorithm, Imaging, Maintenance, Inspection, Computer Vision, and Machine Learning.References
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