Background: Some image compression methods are used to reduce the disc space needed for the image to store and transmit the image efficiently. JPEG is the most frequently used algorithm of compression in medical systems. JPEG compression can be performed at various qualities. There are many other compression algorithms; among these, JPEG2000 is an appropriate candidate to be used in future.
Objective: To investigate perceived image quality of JPEG and JPEG2000 in 1 : 20, 1 : 30, 1 : 40 and 1 : 50 compression rates.
Methods: In total, photographs of 90 patients were taken in dermatology outpatient clinics. For each patient, a set which is composed of eight compressed images and one uncompressed image has been prepared. Images were shown to dermatologists on two separate 17-inch LCD monitors at the same time, with one as compressed image and the other as uncompressed image. Each dermatologist evaluated 720 image couples in total and defined whether there existed any difference between two images in terms of quality. If there was a difference, they reported the better one. Among four dermatologists, each evaluated 720 image couples in total.
Results: Quality rates for JPEG compressions 1 : 20, 1 : 30, 1 : 40 and 1 : 50 were 69%, 35%, 10% and 5% respectively. Quality rates for corresponding JPEG2000 compressions were 77%, 67%, 56% and 53% respectively.
Conclusion: When JPEG and JPEG2000 algorithms were compared, it was observed that JPEG2000 algorithm was more successful than JPEG for all compression rates. However, loss of image quality is recognizable in some of images in all compression rates.
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http://dx.doi.org/10.1111/j.1468-3083.2009.03538.x | DOI Listing |
Braz Oral Res
October 2024
Universidade Estadual de Campinas - Unicamp, Piracicaba Dental School, Department of Oral Diagnosis, Oral Radiology, Piracicaba, SP, Brazil.
Given today's higher demand for online transmission of radiographic images, clinicians and regulatory agencies should be given the evidence they need to guide them in choosing the best image file format to be adopted. To this end, the present scoping review aims to explore, map, and evaluate the literature, with the object of reporting the influence of image file formats on dental diagnostic tasks by assessing intraoral radiographic images. This scoping review complies with PRISMA-ScR.
View Article and Find Full Text PDFUnlabelled: New higher-count-rate, integrating, large area X-ray detectors with framing rates as high as 17,400 images per second are beginning to be available. These will soon be used for specialized MX experiments but will require optimal lossy compression algorithms to enable systems to keep up with data throughput. Some information may be lost.
View Article and Find Full Text PDFThe field of digital holography has been significant developed in recent decades, however, the commercialization of digital holograms is still hindered by the issue of large data sizes. Due to the complex signal characteristics of digital holograms, which are of interferometric nature, traditional codecs are not able to provide satisfactory coding efficiency. Furthermore, in a typical coding scenario, the hologram is encoded and then decoded, leading to a numerical reconstruction via a light wave propagation model.
View Article and Find Full Text PDFSensors (Basel)
October 2022
Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei 10672, Taiwan.
Bayer color filter array (CFA) images are captured by a single-chip image sensor covered with a Bayer CFA pattern which has been widely used in modern digital cameras. In the past two decades, many compression methods have been proposed to compress Bayer CFA images. These compression methods can be roughly divided into the compression-first-based (CF-based) scheme and the demosaicing-first-based (DF-based) scheme.
View Article and Find Full Text PDFJ King Saud Univ Comput Inf Sci
November 2022
The Intelligent Systems Research Group, School of Computing, Telkom University, Jl. Telekomunikasi No. 1, Terusan Buahbatu-Dayeuhkolot, Bandung, West Java 40257 Indonesia.
This study offers an advanced method to evaluate the coronavirus disease 2019 (COVID-19) image quality. The salient COVID-19 image map is incorporated with the deep convolutional neural network (DCNN), namely DeSa COVID-19, which exerts the n-convex method for the full-reference image quality assessment (FR-IQA). The glaring outcomes substantiate that DeSa COVID-19 and the recommended DCNN architecture can convey a remarkable accomplishment on the COVID-chestxray and the COVID-CT datasets, respectively.
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