Lossless Compression of Grayscale and Colour Images Using Multidimensional CSE

Dube, Danny

doi:10.1109/ispa.2019.8868744

Cited by 2 publications

(2 citation statements)

References 17 publications

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“…That is, a pixel in a color image requires total storage of 24 bits. A 24 bit memory can express 2 24 = 16777216 distinct colors. The number of colors should adequately meet the display effect of most images.…”

Section: The Cwdr Methodsmentioning

confidence: 99%

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An Improved Medical Image Compression Method Based on Wavelet Difference Reduction

et al. 2023

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Advanced microscopic techniques such as high-throughput, high-content, multispectral, and 3D imaging could include many images per experiment requiring hundreds of gigabytes (GBs) of memory. Efficient lossy image-compression methods such as joint photographic experts group (JPEG) and JPEG 2000 are crucial to managing these large amounts of data. However, these methods can get visual quality with high compression ratios but do not necessarily maintain the medical data and information integrity. This paper proposes a novel and improved medical image compression method based on color wavelet difference reduction. Specifically, the proposed method is an extension of the standard wavelet difference reduction (WDR) method using mean co-located pixel difference to select the optimum quantity of color images that present the highest similarity in the spatial and temporal domain. The images with large spatiotemporal coherence are encoded as one volume and evaluated regarding the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). The proposed method is evaluated in the challenging histopathological microscopy image analysis field using 31 slides of colorectal cancer. It is found that the perceptual quality of the medical image is remarkably high. The results indicate that the PSNR improvement over existing schemes may reach up to 22.65 dB compared to JPEG 2000. Also, it can reach up to 10.33dB compared to a method utilizing discrete wavelet transform (DWT), leading us to implement a mobile and web platform that can be used for compressing and transmitting microscopic medical images in real time.

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Section: The Cwdr Methodsmentioning

confidence: 99%

“…Recent lossless approaches involve the multi-dimensional compression by substring enumeration (MCSE) by Dubé [24]. CSE is a compression algorithm for bit strings that was generalized to higher dimensions to handle all types of images.…”

Section: Related Workmentioning

confidence: 99%

An Improved Medical Image Compression Method Based on Wavelet Difference Reduction

et al. 2023

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Vision-based environmental perception for autonomous driving

Liu,

Lu,

Lin

2023

Proceedings of the Institution of Mechanical Engineers, Part D:

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Visual perception plays an important role in autonomous driving. One of the primary tasks is object detection and identification. Since the vision sensor is rich in color and texture information, it can quickly and accurately identify various road information. The commonly used technique is based on extracting and calculating various features of the image. The recent development of deep learning-based method has better reliability and processing speed and has a greater advantage in recognizing complex elements. For depth estimation, vision sensor is also used for ranging due to their small size and low cost. Monocular camera uses image data from a single viewpoint as input to estimate object depth. In contrast, stereo vision is based on parallax and matching feature points of different views, and the application of Deep learning also further improves the accuracy. In addition, Simultaneous Location and Mapping (SLAM) can establish a model of the road environment, thus helping the vehicle perceive the surrounding environment and complete the tasks. In this paper, we introduce and compare various methods of object detection and identification, then explain the development of depth estimation and compare various methods based on monocular, stereo, and RGB-D sensors, next review and compare various methods of SLAM, and finally summarize the current problems and present the future development trends of vision technologies.

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Lossless Compression of Grayscale and Colour Images Using Multidimensional CSE

Cited by 2 publications

References 17 publications

An Improved Medical Image Compression Method Based on Wavelet Difference Reduction

An Improved Medical Image Compression Method Based on Wavelet Difference Reduction

Vision-based environmental perception for autonomous driving

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