[PDF] 3D DCT Based Image Compression Method for the Medical Endoscopic Application | Semantic Scholar (2024)

The suggested 3D-Integer DCT-based coder can achieve a higher compression ratio while maintaining the required image quality and needs fewer coefficients to encode an image than the usual Joint Photographic Expert Group (JPEG) coder.

3D-DCT can be applied for creating a video coder much simpler than those following MPEG-x/H.26x and with only slightly less performance.

A new method of compressing digital images by using the Difference Transform applied in medical imaging, which proves to be competitive and in many cases better than the standards used for medical images such as TIFF or PNG.

A novel proposed system for dermoscopic image compression based on the integration of the compression direction-ConvNet (CD-ConvNet) and decompression direction-ConvNet (DD-ConvNet) with discretecosine transform (DCT) and Huffman coding, called DermCompressNet is designed.

Hardware-oriented lossless color filter array (CFA) image compression algorithm based on existing solutions with additional elements increasing the efficiency of the algorithms and elements of other work on which the algorithm is based are presented and characterizes specific optimizations and their impact on the final algorithm result.

A novel image compression algorithm referred to as the Bayer wavelet transform (BWT) algorithm is proposed, which outperformed existing techniques in terms of accuracy, compression ratio, mean square error, peak signal-to-noise ratio, contrast improvement index, and computational time complexity.

The superior RGB-BPSA over existing CS is shown by better visual quality with a higher signal-to-noise ratio (SNR) and structural similarity (SSIM) index in the same CR.

This encryption method realizes the supplementary encryption of hyperspectral images and not only improves the security of encryption, but also reduces the calculation and storage requirements of encrypted data.

The study described the methods of linear data approximation, enabling the removal of distortions at the boundaries of blocks in the lossy compression/reconstruction process, while maintaining high model accuracy and International Hydrographic Organization (IHO) standards.

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An image compression algorithm for wireless capsule endoscopy with high compression rate, low computation complexity and high quality is proposed and a color space transform to de-correlate the R-G1-G2-B color components in the Bayer pattern image is proposed.

An integer discrete-cosine-transform (DCT) based algorithm is presented that works on a low-complexity color-space specially designed for wireless capsule endoscopy application that performs strongly with an average compression ratio of 85% and a high image quality index, peak-signal-to-noise ratio (PSNR) of 52 dB.

The proposed compression scheme has generally superior performance in images where there is substantial amount of background and the proposed quantization table and method for converting a 3D image cube into a ID array provide better coding efficiency in run length coding.

The proposed raster-scan-based data compressor for video capsule endoscopy application performs strongly with a compression ratio of 80% and a very high reconstruction peak signal-to-noise ratio (over 48 dB).

Performance assessment using CFA database shows the proposed design can outperform existing lossless and near-lossless compression algorithms by a large margin, which makes it suitable for capsule endoscopy application.

The results show that the proposed algorithm offers a solution to wireless capsule endoscopy with lossless and yet acceptable level of compression.

This work proposes a two-stage image compression method for wireless capsule endoscopy images to provide high compression rate and high image quality and a simple post-processing for high subjective visual quality of the reconstructed image.

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