Low-Power Endoscopic Image Compression Algorithms Using Modified Golomb Codes

Fante, Kinde Anlay; Bhaumik, Basabi

doi:10.1007/978-981-16-2123-9_5

Advances in Intelligent Systems and Computing

2021

DOI: 10.1007/978-981-16-2123-9_5

|View full text |Cite

Low-Power Endoscopic Image Compression Algorithms Using Modified Golomb Codes

Kinde Anlay Fante

Basabi Bhaumik

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

DermCompressNet: integrated CD-ConvNet and discrete cosine transform for dermoscopic images compression

Elsawy,

Abo-Zahhad,

Wahba

et al. 2024

Multimed Tools Appl

View full text Add to dashboard Cite

Telemedicine has a critical role in healthcare by supporting the information exchange between the patients and the physicians as well as between the physicians for consultation. Such technology has urgent requirements for storage reduction and efficient use of the transmission channel bandwidth. Such requirements can be achieved efficiently via developing accurate medical image compression techniques. For accurate diagnosis, lossless compression methods are recommended. However, the tradeoff between the compression ratio (CR) and the preservation of the image quality is still challenging. On the other hand, the advantages of the convolutional neural networks inspired this work to design 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 discrete cosine transform (DCT) and Huffman coding, called DermCompressNet. To reconstruct a high-quality image at the receiver, the inverse processes using the DD-ConvNet network were followed. The proposed system was evaluated by measuring several image quality metrics, namely the mean square error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM), along with compression quality metrics, namely CR, and computational time (CT). The experimental results achieved 34.6 dB, 2.5, 0.85, and 56% of PSNR, MSE, SSIM, and CR, respectively. A comparison studies with the JPEG and state-of-the-art methods proved the superiority of the proposed system, showing23%, 16%, 4.3%, and 1.8% improvements in the PSNR, MSE, SSIM, and CR, respectively, compared to the JPEG.

show abstract

DermCompressNet: integrated CD-ConvNet and discrete cosine transform for dermoscopic images compression

Elsawy,

Abo-Zahhad,

Wahba

et al. 2024

Multimed Tools Appl

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Low-Power Endoscopic Image Compression Algorithms Using Modified Golomb Codes

Cited by 1 publication

References 20 publications

DermCompressNet: integrated CD-ConvNet and discrete cosine transform for dermoscopic images compression

DermCompressNet: integrated CD-ConvNet and discrete cosine transform for dermoscopic images compression

Contact Info

Product

Resources

About