Psychophysical and metric assessment of fused images
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The prevalence of image fusion - the fusing of images of different modalities, such as visible and infrared radiation - has increased the demand for accurate methods of image quality assessment. Two traditional methods of assessment that have been used are computational metrics and subjective quality assessment; we propose an alternative task-based method of image assessment, which represents a more accurate description of image 'quality' than subjective ratings. The current study used a signal detection paradigm, identifying the presence or absence of a target in briefly presented images followed by an energy mask, which was compared with computational metric results. In Experiment 1, 18 participants were presented with composites of fused infrared and visible light images, with a soldier either present or not. There were two independent variables, each with three levels: image fusion method (averaging, contrast pyramid, dual-tree complex wavelet transform), and JPEG2000 compression (no compression, low, and high compression), in a repeated measures design. Participants were presented with images and asked to state whether or not they detected the target. In addition, metric results were calculated and compared with task performance. Images were blocked by fusion type, with compression type randomised within blocks. This process was repeated in Experiment 2, but with JPEG images substituted for JPEG2000. The results showed a significant effect for fusion but not compression in JPEG2000 images, whilst JPEG images showed significant effects for both fusion and compression. The metric results for both JPEG and JPEG2000 showed similar trends with more advanced metrics matching the performance of the psychophysical tests more accurately.Keywords:
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In this study, the performances of JPEG (the most widely used lossy image compression standard until it was published in 1992), JPEG2000 (designed to provide superior image quality at low bit rates) and JPEG XR (aimed to reach the speed of JPEG and the quality of JPEG2000) are evaluated with an application developed in C# language which is able to use different codecs. The results show that recently developed JPEG standard (JPEG XR) is able to compress images with the same quality as JPEG2000, but not the same speed as JPEG.
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In this chapter, we have described the JPEG standard for still image compression. We discussed the details of the algorithm for lossless JPEG. We have also discussed in great detail the principles and algorithms for the baseline JPEG standard. Baseline JPEG is the most used and popular algorithm amongst all different modes in JPEG standard for still image compression. We have presented some results of baseline JPEG and compared with the new JPEG2000 standard. The features, concepts, and principles behind the algorithms for JPEG2000 standard will be elaborated in great detail in Chapters 6, 7, 8 and 10. We also summarized the progressive mode and hierarchical mode of operation of the JPEG standard in this chapter with examples.
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The 93rd JPEG meeting was held online from 18 to 22 October 2021. The JPEG Committee continued its work on the development of new standardised solutions for the representation of visual information. Notably, the JPEG Committee has decided to release a new call for proposals on point cloud coding based on machine learning technologies that targets both compression efficiency and effective performance for 3D processing as well as machine and computer vision tasks. This activity will be conducted in parallel with JPEG AI standardization. Furthermore, it was also decided to pursue the development of a new standard in the context of the exploration on JPEG Fake News activity.
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Abstract 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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The Joint Photographic Experts Group (JPEG) is currently in the process of standardizing JPEG XL, the next generation image coding standard that o↵ers substantially better compression efficiency than existing image formats. In this paper, the quality assessment framework of proposals submitted to the JPEG XL Call for Proposals is presented in details. The proponents were evaluated using objective metrics and subjective quality experiments in three di↵erent laboratories, on a dataset constructed for JPEG XL quality assessment. Subjective results were analyzed using statistical significance tests and presented with correlation measures between the results obtained from di↵erent labs. Results indicate that a number of proponents superseded the JPEG standard and performed at least as good as the state-of-the-art anchors in terms of both subjective and objective quality on SDR and HDR contents, at various bitrates.
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The original JPEG compression standard is efficient at low to medium levels of compression with relatively low levels of loss in visual image quality and has found widespread use in the imaging industry. Excessive compression using JPEG however, results in well-known artifacts such as "blocking" and "ringing," and the variation in image quality as a result of differing scene content is well documented. JPEG 2000 has been developed to improve on JPEG in terms of functionality and image quality at lower bit rates. One of the more fundamental changes is the use of a discrete wavelet transform instead of a discrete cosine transform, which provides several advantages both in terms of the way in which the image is encoded and overall image quality. This study involves a comparison of subjective image quality between JPEG and JPEG 2000 to establish whether JPEG 2000 does indeed demonstrate significant improvements in visual quality. A particular focus of this work is the inherent scene dependency of the two algorithms and their influence on subjective image quality results. Further work on the characterization of scene content is carried out in a connected study [S. Triantaphillidou, E. Allen, and R. E. Jacobson, “Image quality comparison between JPEG and JPEG2000. II. Scene dependency, scene analysis, and classification”, J. Imaging Sci. Technol. 51, 259 (2007)]. © 2007 Society for Imaging Science and Technology.
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The International Standardization Committee ISO/IEC JTC1 SC29 WG1, better known as the Joint Photographic Experts Group (JPEG), has a long tradition in the creation of image coding standards. More than 27 years after the release of the first JPEG standard ISO/IEC 10918, the JPEG format stands as a synonym for digital pictures.
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Subjective evaluation of compressed image quality on computer displays was studied,in order to realize quality evaluation of compressed images on the Internet.The relative studies include: to set-up displays,to put forward assessment scales for static compressed images based on the standard of subjective assessment of quality for color TV pictures,and to collect color images and establish a database for subjective evaluation.As an example for testing above studies,by using a psychophysical method of pairwise comparison,subjective evaluation experiments on optimal compression ratio of JPEG and JPEG2000 were conducted on displays for the images,which were from JPEG and lossy JPEG2000 with seven compression ratios.Ten subjects took part in the experiments,and 280 color images for 20 scenes with different contents were used.The experimental results showed that optimal compression ratio range of JPEG is from 20∶1 to 25∶1,and optimal compression ratio range of JPEG2000 is from 25∶1 to 30∶1.The experiments indicated that the display set-up by human eyes can achieve consistency for subjective evaluation of image quality on displays.
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The aim of this paper is to compare the quality of digitized chest X-ray images with digitally captured chest X-ray images in children with lung tuberculosis (TB), compressed using popular JPEG and JPEG2000 compression algorithms, for further electronic correspondence. All images were compressed using JPEG and JPEG2000 compression algorithms with six different compression degrees (3 bpp, 1.5 bpp, 1 bpp, 0.7 bpp, 0.5 bpp, 0.3 bpp). Picture quality was evaluated by means of usual objective measures of picture quality such as MSE, SNR and PSNR. All compressed images were shown to physicians, who were asked to evaluate diagnostic accuracy of each image (by poor, good or excellent). According to physician's subjective evaluation both JPEG and JPEG2000 compression for all X-ray digitized images (all TB-attributes) were accepted as excellent
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This paper describes an objective comparison of the image quality of different encoders. Our approach is based on estimating the visual impact of compression artifacts on perceived quality. We present a tool that measures these artifacts in an image and uses them to compute a prediction of the Mean Opinion Score (MOS) obtained in subjective experiments. We show that the MOS predictions by our proposed tool are a better indicator of perceived image quality than PSNR, especially for highly compressed images. For the encoder comparison, we compress a set of 29 test images with two JPEG encoders (Adobe Photoshop and IrfanView) and three JPEG2000 encoders (JasPer, Kakadu, and IrfanView) at various compression ratios. We compute blockiness, blur, and MOS predictions as well as PSNR of the compressed images. Our results show that the IrfanView JPEG encoder produces consistently better images than the Adobe Photoshop JPEG encoder at the same data rate. The differences between the JPEG2000 encoders in our test are less pronounced; JasPer comes out as the best codec, closely followed by IrfanView and Kakadu. Comparing the JPEG- and JPEG2000-encoding quality of IrfanView, we find that JPEG has a slight edge at low compression ratios, while JPEG2000 is the clear winner at medium and high compression ratios.
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