scholarly journals Satellite Image Compression Technique Based on the Evidence Theory

2014 ◽  
Vol 5 (1) ◽  
pp. 17-23 ◽  
Author(s):  
Khaled Sahnoun ◽  
Noureddine Benabadji
Keyword(s):  
Image Compression ◽  
Satellite Image ◽  
Evidence Theory ◽  
Compression Technique

Quantization Encoding Algorithm Based Satellite Image Compression

2017 ◽  
Vol 8 (3) ◽  
pp. 740
Author(s):  
Anand M ◽  
V. Mathivananr
Keyword(s):  
Image Compression ◽  
Satellite Images ◽  
Satellite Image ◽  
Region Of Interest ◽  
Digital Data ◽  
Storage Space ◽  
Compression Process ◽  
Compression Technique ◽  
Transmission Bandwidth ◽  
Image Technique

In the field of digital data there is a demand in bandwidth for the transmission of the videos and images all over the worlds. So in order to reduce the storage space in the field of image applications there is need for the image compression process with lesser transmission bandwidth. So in this paper we are proposing a new image compression technique for the compression of the satellite images by using the Region of Interest (ROI) based on the lossy image technique called the Quantization encoding algorithm for the compression. The performance of our method can be evaluated and analyzing the PSNR values of the output images.

scholarly journals Two-dimensional satellite image compression using compressive sensing

2022 ◽  
Vol 12 (1) ◽  
pp. 311
Author(s):  
Gunasheela Keragodu Shivanna ◽  
Haranahalli Shreenivasamurthy Prasantha
Keyword(s):  
Image Compression ◽  
Compressive Sensing ◽  
Satellite Image ◽  
Research Community ◽  
Reconstruction Accuracy ◽  
Promising Technique ◽  
Compression Technique ◽  
Satellite Imaging ◽  
Compression Algorithms ◽  
Ground Station

Compressive sensing is receiving a lot of attention from the image processing research community as a promising technique for image recovery from very few samples. The modality of compressive sensing technique is very useful in the applications where it is not feasible to acquire many samples. It is also prominently useful in satellite imaging applications since it drastically reduces the number of input samples thereby reducing the storage and communication bandwidth required to store and transmit the data into the ground station. In this paper, an interior point-based method is used to recover the entire satellite image from compressive sensing samples. The compression results obtained are compared with the compression results from conventional satellite image compression algorithms. The results demonstrate the increase in reconstruction accuracy as well as higher compression rate in case of compressive sensing-based compression technique.

scholarly journals The Evidence Theory for Color Satellite Image Compression

2014 ◽  
Author(s):  
Khaled SAHNOUN ◽  
Noureddine BENABADJI
Keyword(s):  
Image Compression ◽  
Satellite Image ◽  
Evidence Theory

scholarly journals Modifying fractal image compression technique by hybridation of crowding genetic algorithm and scattered method

2021 ◽  
Author(s):  
Shaimaa S. Al-Bundi ◽  
Karrar Q. AL-Jubouri ◽  
Nadia M. G. Al-Saidi
Keyword(s):  
Genetic Algorithm ◽  
Image Compression ◽  
Fractal Image Compression ◽  
Compression Technique ◽  
Fractal Image

Application of wavelet packet image compression technique to particle image velocimetry

2002 ◽  
Vol 15 (1-4) ◽  
pp. 383-392 ◽  
Author(s):  
Hui Li ◽  
Yoshifuru xTakei ◽  
Yoshifuru Saito ◽  
Kiyoshi Horii
Keyword(s):  
Particle Image Velocimetry ◽  
Image Compression ◽  
Particle Image ◽  
Wavelet Packet ◽  
Compression Technique ◽  
Image Velocimetry

Efficient Domain Search for Fractal Image Compression Using Feature Extraction Technique

2012 ◽  
Vol 488-489 ◽  
pp. 1587-1591
Author(s):  
Amol G. Baviskar ◽  
S. S. Pawale
Keyword(s):  
Feature Extraction ◽  
Image Compression ◽  
Low Complexity ◽  
Contractive Mapping ◽  
Fractal Image Compression ◽  
Compression Technique ◽  
Image Encoding ◽  
Fractal Image ◽  
Coding Method ◽  
The Given

Fractal image compression is a lossy compression technique developed in the early 1990s. It makes use of the local self-similarity property existing in an image and finds a contractive mapping affine transformation (fractal transform) T, such that the fixed point of T is close to the given image in a suitable metric. It has generated much interest due to its promise of high compression ratios with good decompression quality. Image encoding based on fractal block-coding method relies on assumption that image redundancy can be efficiently exploited through block-self transformability. It has shown promise in producing high fidelity, resolution independent images. The low complexity of decoding process also suggested use in real time applications. The high encoding time, in combination with patents on technology have unfortunately discouraged results. In this paper, we have proposed efficient domain search technique using feature extraction for the encoding of fractal image which reduces encoding-decoding time and proposed technique improves quality of compressed image.

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