Medical image compression framework based on compressive sensing, DCT and DWT

Kher, Rahul; Patel, Yamini

doi:10.15761/bem.1000114

Cited by 5 publications

(3 citation statements)

References 5 publications

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“…In terms of time complexity, DCT is favored for its relatively fast compression speeds. 39 However, the computational cost of combined SVD and DWT may be slightly higher due to the additional steps involved in both techniques. Despite this, the benefits of enhanced compression efficiency and image fidelity outweigh the marginal increase in processing time.…”

Section: Integration Of Svd and Dwt (Haar)techniquesmentioning

confidence: 99%

Adaptive image compression for vehicular ad hoc networks: a discrete wavelet transform low-low subband (DWT-LL), singular value decomposition (SVD), and linear programming (LP) approach for vehicle density sensing-based compression

Okpok,

Kihei

2024

Autonomous Systems: Sensors, Processing, and Security for Ground, Air, Sea, and Space Vehicles and Infrastructure 2024

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This research presents a novel technique for image compression and transmission tailored for Vehicular Ad Hoc Networks (VANETs), emphasizing the adaptation of Modulation and Coding schemes (MCS) to suit compression ratio demands contingent on vehicle density around roadside units. Leveraging Discrete Wavelet Transform Low-Low subband (DWT LL), Singular Value Decomposition (SVD), and Linear Programming (LP), the proposed technique dynamically adjusts compression ratios based on vehicular presence. Consequently, it enables simultaneous modulation of MCS and image compression, uniquely customizing images for VANET applications. Compression ratios ranging from 47.01% to 74.1% are achieved, correlating with vehicle density near Roadside units, satisfying size constraints crucial for efficient Infrastructure to Vehicles (I2V) image message dissemination within a 300-meter radius accommodating up to 200 vehicles. This adaptive approach holds promise for delivering image-enhanced public emergency notifications within the transportation sector, offering a viable solution for real-time communication and enhancing situational awareness amidst dynamic vehicular environments.

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Section: Integration Of Svd and Dwt (Haar)techniquesmentioning

confidence: 99%

Adaptive image compression for vehicular ad hoc networks: a discrete wavelet transform low-low subband (DWT-LL), singular value decomposition (SVD), and linear programming (LP) approach for vehicle density sensing-based compression

Okpok,

Kihei

2024

Autonomous Systems: Sensors, Processing, and Security for Ground, Air, Sea, and Space Vehicles and Infrastructure 2024

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“…There are many basis functions that are used for sparse representation of a signal. The widely used basis functions are discrete wavelets transform (DWT) and discrete cosine transform (DCT) [55].…”

Section: B Sparse Representationmentioning

confidence: 99%

Compressive Sensing Based Active Imaging System Using Programable Coded Mask and a Photodiode

2023

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There has been significant progress in the field of compressive sensing (CS) and its applications in various fields in recent years. Here, we have developed a CS-based active imaging system that does not require a pixelated array detector but instead uses a transmissive spatial light modulator as a programmable coded mask. Single-pixel cameras (SPCs) have many applications in fields such as terahertz (THz) and infrared (IR) imaging. With an increase in the number of pixels, array detectors can become expensive, especially in the THz and IR regimes. In this article, we have explored the concept of active illumination, which could be helpful in developing SPCs. The article focuses on the development of an active SPC, and the analysis of how coded masks affect the quality of the reconstructed image.

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“…Several authors have used DCT for compression of medical images. [ 4 5 6 7 ] However, compression of NM images using DCT has not gained much attention. In this pilot study, we have performed the compression of 99m Tc methylene diphosphonate (MDP) bone scan images using DCT.…”

Section: Introductionmentioning

confidence: 99%

Compression of ^99mTC methylene diphosphonate bone scan images using discrete cosine transformation

et al. 2022

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Aims and Objectives: The objective of this study was to find the optimum value of threshold for compression of 99m Tc-methylene diphosphonate (MDP) bone scan images using discrete cosine transformation (DCT). Materials and Methods: DCT was applied to 51 99m Tc-MDP bone scan images and then the image of logarithmic value of DCT coefficients was inspected to determine the threshold. After inspecting the number of images of DCT coefficients, we estimated the appropriate value of the threshold to be 10. After the application of threshold = 10, compressed image was reconstructed by applying the inverse DCT. Compression factor was calculated by dividing the nonzero element after thresholding to the nonzero element before thresholding DCT coefficients. Nuclear medicine physicians compared the compressed images with its input images and labeled them as acceptable or unacceptable. During comparison of input and compressed images, we considered points such as smoothening, blocking artifacts, body contour, gap between closely placed lesions, and detectability of lesion. Results: Forty-four compressed images (out of 51 images) obtained at threshold 10 were acceptable to Nuclear Medicine Physician (NMP). Compressed images were less noisy compared to its input image. Compression factor was found to be 13.03 ± (minimum = 2.71, maximum = 42.92). Conclusion: The optimum value of threshold for compression of 99m Tc-MDP bone scan images was found to be 10, and the average compression factor achieved was equal to 13.03 (92.30%).

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Medical image compression framework based on compressive sensing, DCT and DWT

Cited by 5 publications

References 5 publications

Adaptive image compression for vehicular ad hoc networks: a discrete wavelet transform low-low subband (DWT-LL), singular value decomposition (SVD), and linear programming (LP) approach for vehicle density sensing-based compression

Adaptive image compression for vehicular ad hoc networks: a discrete wavelet transform low-low subband (DWT-LL), singular value decomposition (SVD), and linear programming (LP) approach for vehicle density sensing-based compression

Compressive Sensing Based Active Imaging System Using Programable Coded Mask and a Photodiode

Compression of ^99mTC methylene diphosphonate bone scan images using discrete cosine transformation

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Medical image compression framework based on compressive sensing, DCT and DWT

Cited by 5 publications

References 5 publications

Adaptive image compression for vehicular ad hoc networks: a discrete wavelet transform low-low subband (DWT-LL), singular value decomposition (SVD), and linear programming (LP) approach for vehicle density sensing-based compression

Adaptive image compression for vehicular ad hoc networks: a discrete wavelet transform low-low subband (DWT-LL), singular value decomposition (SVD), and linear programming (LP) approach for vehicle density sensing-based compression

Compressive Sensing Based Active Imaging System Using Programable Coded Mask and a Photodiode

Compression of 99mTC methylene diphosphonate bone scan images using discrete cosine transformation

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Compression of ^99mTC methylene diphosphonate bone scan images using discrete cosine transformation