The Imatest program: comparing cameras with different amounts of sharpening

Koren, Norman L.

doi:10.1117/12.650848

Cited by 27 publications

(17 citation statements)

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“…4a and 4b show hole images obtained by taking pictures of perforated black board using bright backlight with normal-and underexposures, respectively [6]. CA measurement, area between highest color value and lowest color value over edge, is obtained by software, Imatest [11]. The lower CA measurement is, the less color fringe appears.…”

Section: Resultsmentioning

confidence: 99%

Color fringe correction based on image fusion

Jang

Kim

Jung

et al. 2014

2014 IEEE International Conference on Image Processing (ICIP)

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This paper proposes an image fusion based method for color fringe correction. Color fringes are frequently observed at high contrast edges, i.e., a brighter image has more color fringe than a darker image. The proposed color fringe correction method fuses pixel values of the normal-exposure image with color fringe and the under-exposure image with no color fringe. First, each of normal-and under-exposure images is transformed using a color difference model. Second, color fringe regions are detected and used for calculating fusion weights. Third, the color difference values are fused with the weights refined by guided filtering. Experimental results show that the proposed fusion-based method preserves better an original color in color fringe regions than existing methods.

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Section: Resultsmentioning

confidence: 99%

Color fringe correction based on image fusion

Jang

Kim

Jung

et al. 2014

2014 IEEE International Conference on Image Processing (ICIP)

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“…The last choice is appropriate when the digital sensor sizes vary widely from small in camera phones to large for full-frame professional cameras. In [46], the author has argued that the MTF50 value of the frequency response correlates well with the perceived sharpness.…”

Section: Image Sharpness and Resolutionmentioning

confidence: 99%

Image Quality Assessment of Digital Image Capturing Devices for Melanoma Detection

Dugonik

Marovt

et al. 2020

Applied Sciences

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The fast-growing incidence of skin cancer, especially melanoma, is the guiding principle for intense development of various digital image-capturing devices providing easier recognition of melanoma by dermatologists. Handheld and digital dermoscopy, following of mole changes with smartphones and digital analysing of mole images, is based on evaluation of the colours, shape and deep structures in the skin moles. Incorrect colour information of an image, under- or overexposed images, lack of sharpness and low resolution of the images, can lead to melanoma misdiagnosis. The purpose of our study was to determine the colour error in the image according to the given lighting conditions and different camera settings. We focused on measuring the image quality parameters of smartphones and high-resolution cameras to compare them with the results of state-of-the-art dermoscopy device systems. We applied standardised measuring methods. The spatial frequency response method was applied for measuring the sharpness and resolution of the tested camera systems. Colour images with known reference values were captured from the test target, to evaluate colour error as a CIELAB (Commission Internationale de l’Eclairage) ΔE*ab colour difference as seen by a human observer. The results of our measurements yielded two significant findings. First, all tested cameras produced inaccurate colours when operating in automatic mode, and second, the amount of sharpening was too intensive. These deficiencies can be eliminated through adjusting the camera parameters manually or by image post-production. The presented two-step camera calibration procedure improves the colour accuracy of captured clinical and dermoscopy images significantly.

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“…The Imatest program was used to obtain the key image quality factors in MD cameras discussed in Section 2. The program was used to compute tonal response (OECF) measurements for different density values of the test chart [38].…”

Section: Details Of the Objective Studymentioning

confidence: 99%

Effective Dynamic Range Evaluation of Digital Still Images in Mobile Devices

et al. 2019

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Digital photography has immersed in everyday surroundings through mobile devices which became the most popular tool for taking pictures. However, the compactness of these devices is an obstacle for certain image quality parameters when it comes to usability. The purpose of this paper is to analyze the effective dynamic range of mobile device cameras. We obtained opto-electric conversion function (OECF) measurements according to ISO standard for total and effective dynamic range evaluation. Additionally, the evaluation of effective dynamic range using high dynamic range image construction was performed where algorithms for tone mapping were applied. Our findings indicate little difference in OECF values among different mobile device cameras, as well as for the total dynamic range values. However, when it comes to the effective dynamic range, cameras in these devices show less input-output conversion stability. Additionally, tone mapping indicates that the effective dynamic range is different between devices.

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The Imatest program: comparing cameras with different amounts of sharpening

Cited by 27 publications

References 0 publications

Color fringe correction based on image fusion

Color fringe correction based on image fusion

Image Quality Assessment of Digital Image Capturing Devices for Melanoma Detection

Effective Dynamic Range Evaluation of Digital Still Images in Mobile Devices

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