Two-stage wireless capsule image compression with low complexity and high quality

2012 ◽  
Vol 48 (25) ◽  
pp. 1588-1589 ◽  
Author(s):  
Yingke Gu ◽  
Xiang Xie ◽  
Zhihua Wang ◽  
Guolin Li ◽  
Tianjia Sun
Keyword(s):  
Image Compression ◽  
Low Complexity ◽  
High Quality ◽  
Two Stage ◽  
Wireless Capsule

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.

Temperature-programmed nitridation of monodispersed VOx nanoparticles into nanocrystalline superconducting oxygen-doped vanadium nitride

2021 ◽  
Author(s):  
Khemchand Dewangan ◽  
Dadan Singh ◽  
Sandeep Kumar Singh Patel ◽  
Kamlesh Kumar Shrivas
Keyword(s):  
Thermal Decomposition ◽  
Synthesis Process ◽  
Vanadium Nitride ◽  
High Quality ◽  
Two Stage ◽  
Stage Synthesis ◽  
Temperature Programmed ◽  
Superconducting Applications

A two-stage synthesis process was employed to prepare high-quality nanocrystalline vanadium nitride (VN) for superconducting applications. Firstly, monodispersed amorphous VOx nanoparticles were obtained via thermal-decomposition of vanadium (III) acetylacetonate [V(acac)3]...

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.

Low-Complexity Approaches for Lossless and Near-Lossless Hyperspectral Image Compression

2011 ◽  
pp. 47-65
Author(s):  
Andrea Abrardo ◽  
Mauro Barni ◽  
Andrea Bertoli ◽  
Raoul Grimoldi ◽  
Enrico Magli ◽  
...  
Keyword(s):  
Image Compression ◽  
Hyperspectral Image ◽  
Low Complexity ◽  
Hyperspectral Image Compression
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