Evaluation of perceived image sharpness with changes in the displayed image size

Park, Jae Young; Triantaphillidou, Sophie; Jacobson, Ralph E.; Gupta, Gaurav

doi:10.1117/12.908201

Cited by 2 publications

(3 citation statements)

References 9 publications

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“…A total of sixteen large size average scenes 22 and their corresponding smaller versions, one unmodified and one contrast modified version according to previous finding, were used. Observers were asked to asked to rate the test image pair in terms of their appearance matching (from 10 being the most matching to 1 being the least matching).…”

Section: Validation Of the Resultsmentioning

confidence: 99%

“…They are presented in Figure 10, calibrated in a sharpness JND scale 22 . The linear trend line shows the relationship as: y = -0.159x-0.069 with R² = 0.995.…”

Section: Changes In Perceived Contrast Vs Changes In Perceived Sharpnessmentioning

confidence: 99%

“…In a recent study 1 , a series of psychophysical experiments were carried out to quantify changes in perceived sharpness with respect to changes in displayed image size. Results from the sharpness matching experiment showed that perceived sharpness increased when image size was decreased, but the magnitude of the perceived differences was scene dependent.…”

Section: Introductionmentioning

confidence: 99%

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Just noticeable differences in perceived image contrast with changes in displayed image size

2014

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An evaluation of the change in perceived image contrast with changes in displayed image size was carried out. This was achieved using data from four psychophysical investigations, which employed techniques to match the perceived contrast of displayed images of five different sizes. A total of twenty-four S-shape polynomial functions were created and applied to every original test image to produce images with different contrast levels. The objective contrast related to each function was evaluated from the gradient of the mid-section of the curve (gamma). The manipulation technique took into account published gamma differences that produced a just-noticeable-difference (JND) in perceived contrast. The filters were designed to achieve approximately half a JND, whilst keeping the mean image luminance unaltered. The processed images were then used as test series in a contrast matching experiment. Sixty-four natural scenes, with varying scene content acquired under various illumination conditions, were selected from a larger set captured for the purpose. Results showed that the degree of change in contrast between images of different sizes varied with scene content but was not as important as equivalent perceived changes in sharpness 1 .

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Section: Validation Of the Resultsmentioning

confidence: 99%

“…They are presented in Figure 10, calibrated in a sharpness JND scale 22 . The linear trend line shows the relationship as: y = -0.159x-0.069 with R² = 0.995.…”

Section: Changes In Perceived Contrast Vs Changes In Perceived Sharpnessmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Just noticeable differences in perceived image contrast with changes in displayed image size

2014

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Quality Assessment of Sharpened Images: Challenges, Methodology, and Objective Metrics

Krasula

Callet

Fliegel

et al. 2017

IEEE Trans. on Image Process.

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Most of the effort in image quality assessment (QA) has been so far dedicated to the degradation of the image. However, there are also many algorithms in the image processing chain that can enhance the quality of an input image. These include procedures for contrast enhancement, deblurring, sharpening, up-sampling, denoising, transfer function compensation, etc. In this work, possible strategies for the quality assessment of sharpened images are investigated. This task is not trivial because the sharpening techniques can increase the perceived quality, as well as introduce artifacts leading to the quality drop (over-sharpening). Here, the framework specifically adapted for the quality assessment of sharpened images and objective metrics comparison in this context is introduced. However, the framework can be adopted in other quality assessment areas as well. The problem of selecting the correct procedure for subjective evaluation was addressed and a subjective test on blurred, sharpened, and over-sharpened images was performed in order to demonstrate the use of the framework. The obtained ground-truth data were used for testing the suitability of state-ofthe- art objective quality metrics for the assessment of sharpened images. The comparison was performed by novel procedure using ROC analyses which is found more appropriate for the task than standard methods. Furthermore, seven possible augmentations of the no-reference S3 metric adapted for sharpened images are proposed. The performance of the metric is significantly improved and also superior over the rest of the tested quality criteria with respect to the subjective data.

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Evaluation of perceived image sharpness with changes in the displayed image size

Cited by 2 publications

References 9 publications

Just noticeable differences in perceived image contrast with changes in displayed image size

Just noticeable differences in perceived image contrast with changes in displayed image size

Quality Assessment of Sharpened Images: Challenges, Methodology, and Objective Metrics

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