Image quality estimation for different spatial resolutions

Demirtas, Ali Murat; Reibman, Amy R.; Jafarkhani, Hamid

doi:10.1109/icip.2013.6738078

Cited by 2 publications

(2 citation statements)

References 15 publications

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“…For images of different resolutions, there are two common simple approaches: downscaling the higher resolution image, or upscaling the lower resolution one [Demirtas et al 2014]. Since we do not want to lose the information present in H, we upscale D. We call this upscaled image X, which has the same dimensions as H. Assuming a piecewise constant interpolation, each pixel of D is replicated in s 2 pixels of X (Figure 3, top).…”

Section: The Downscaling Problemmentioning

confidence: 99%

Perceptually based downscaling of images

Öztireli

Groß

2015

ACM Trans. Graph.

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We propose a perceptually based method for downscaling images that provides a better apparent depiction of the input image. We formulate image downscaling as an optimization problem where the difference between the input and output images is measured using a widely adopted perceptual image quality metric. The downscaled images retain perceptually important features and details, resulting in an accurate and spatio-temporally consistent representation of the high resolution input. We derive the solution of the optimization problem in closed-form, which leads to a simple, efficient and parallelizable implementation with sums and convolutions. The algorithm has running times similar to linear filtering and is orders of magnitude faster than the state-of-the-art for image downscaling. We validate the effectiveness of the technique with extensive tests on many images, video, and by performing a user study, which indicates a clear preference for the results of the new algorithm.

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Section: The Downscaling Problemmentioning

confidence: 99%

Perceptually based downscaling of images

Öztireli

Groß

2015

ACM Trans. Graph.

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“…Another subjective study conducted in [17] tries to measure the quality of distorted image with a lower resolution compared to the reference image. In this study, 24 images are employed and distorted with JPEG, JPEG 2000, blurriness, or noisiness, and viewers are asked to choose preference for displayed image pair.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of image quality of experience in consideration of viewing distance

Fang

Shen

2015

2015 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP)

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Image viewing distance plays an important role in the assessment of image Quality of Experience (QoE). In this work, we present a subjective image QoE study in which a total of 494 images evaluated by more than 30 human subjects at 7 different viewing distance. Through the study, we observed that different images have different regularities between viewing distance and their QoE. A No-Reference QoE assessment model is proposed to objectively measure image QoE considering viewing distance. The experiments conducted on our database show that the proposed model achieves high correlation between its predicted QoE score and human perception. Moreover, we have made the image database freely available to the research community.

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Image quality estimation for different spatial resolutions

Cited by 2 publications

References 15 publications

Perceptually based downscaling of images

Perceptually based downscaling of images

Evaluation of image quality of experience in consideration of viewing distance

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