Objective assessment of perceived sharpness of projection displays with a calibrated camera

Zhao, Ping; Cheng, Yang; Pedersen, Marius

doi:10.1109/cvcs.2015.7274892

Cited by 7 publications

(9 citation statements)

References 36 publications

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“…Future works include evaluation of a physical setup with several displays, different orientations and overlapping ratio. Evaluation can also be done using a calibrated digital camera [63][64]. Moreover, investigation to reduce the streaking issues can be investigated.…”

Section: Resultsmentioning

confidence: 99%

Seam-Based Edge Blending for Multi-Projection Systems

Pedersen¹,

Suazo²,

Thomas³

2016

IJSIP

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Section: Resultsmentioning

confidence: 99%

Seam-Based Edge Blending for Multi-Projection Systems

Pedersen¹,

Suazo²,

Thomas³

2016

IJSIP

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“…Captured pictures are known to have a vignetting effect, namely an undesirable gradual intensity fall off from the image center to its external limits. We incorporated the method proposed in our previous research 44 to correct camera vignetting based on the captures of a hazy sky which is closely uniform in gray.…”

Section: Objective Experimentsmentioning

confidence: 99%

Measuring the Relative Image Contrast of Projection Displays

Zhao¹,

Pedersen²,

Hardeberg³

et al. 2015

jist

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International audienceProjection displays, compared to other modern display technologies, have many unique advantages. However, the image quality assessment of projection displays has not been well studied so far. In this paper, we propose an objective approach to measure the relative contrast of projection displays based on the pictures taken with a calibrated digital camera in a dark room where the projector is the only light source. A set of carefully selected natural images is modified to generate multiple levels of image contrast. In order to enhance the validity, reliability, and robustness of our research, we performed the experiments in similar viewing conditions at two separate geographical locations with different projection displays. In each location, we had a group of observers to give perceptual ratings. Further, we adopted state-of-art contrast measures to evaluate the relative contrast of the acquired images. The experimental results suggest that the Michelson contrast measure performs the worst, as expected, while other global contrast measures perform relatively better, but they have less correlation with the perceptual ratings than local contrast measures. The local contrast measures perform better than global contrast measures for all test images, but all contrast measures failed on the test images with low luminance or dominant colors and without texture areas. In addition, the high correlations between the experimental results for the two projections displays indicate that our proposed assessment approach is valid, reliable, and consistent

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“…22 naive human observers (10 men and 12 women, age [20][21][22][23][24][25][26][27], following the recommendation of minimum 15 observers by CIE [59] and ITU [60], were invited to give perceptual ratings to the different levels sharpness of images using a five force-choice based category judgment. The five categories, bad, poor, fair, good, and excellent, were represented by numbers from 1 to 5.…”

Section: Methodsmentioning

confidence: 99%

“…Amirshahi et al [26] proposed an IQ metric based on features extracted from Convolutional Neural Networks (CNNs), which produced good results on different databases. Zhao et al [27] evaluated IQ metrics for perceived sharpness of projection displays, where the images were blurred, and found that SSIM, FSIM and VIF produced good results.…”

Section: ) Full Reference Metricsmentioning

confidence: 99%

Evaluation of image quality metrics for sharpness enhancement

Cheng

Pedersen

Chen

2017

Proceedings of the 10th International Symposium on Image and Signal Processing and Analysis

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Abstract-Image quality assessment has become a meaningful research field due to the explosive growth of image processing technologies in imaging industries. It is becoming more usual to quantify the quality of an image using image quality metrics, rather than carrying out time-consuming psychometric experiments. However, there is little research on the performance of image quality metrics on quality enhanced images. In this paper, we focus on images that have been enhanced by sharpening. A psychometric experiment was designed with observers giving scores to different images enhanced by sharpening on a display in a controlled dark environment. The results showed that full reference image quality metrics performed well when sharpening did not improve the visual image quality, while in images where sharpening increased the visual quality the performance was lower. No reference image quality metrics show better predictions than full reference image quality metrics in most cases.

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Objective assessment of perceived sharpness of projection displays with a calibrated camera

Cited by 7 publications

References 36 publications

Seam-Based Edge Blending for Multi-Projection Systems

Seam-Based Edge Blending for Multi-Projection Systems

Measuring the Relative Image Contrast of Projection Displays

Evaluation of image quality metrics for sharpness enhancement

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