Perceptual image quality assessment using a normalized Laplacian pyramid

Laparra, Valero; Ballé, Johannes; Berardino, Alexander; Simoncelli, Eero P.

doi:10.2352/issn.2470-1173.2016.16.hvei-103

Cited by 135 publications

(103 citation statements)

References 30 publications

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“…We also evaluate the feature similarity index (FSIM) [ZZMZ11], which uses gradient information to examine low-level features, as well as the more recent gradient magnitude similarity deviation (GMSD) [XZMB14] approach, which also focuses on local gradient similarities. Finally, we include the recently developed normalized Laplacian pyramid distance (NLP-dist), which is essentially a root mean-square error (RMSE) in a multi-scale decomposition or "normalized Laplacian" domain [LBBS16]. We note that our primary interest in this evaluation is to find an IQA that most agrees with the perceptual scores from our user study (described in the following section) on CESM data, and thus we ignore the cost of applying the IQA measures at this time.…”

Section: Image Quality Measuresmentioning

confidence: 99%

Evaluating image quality measures to assess the impact of lossy data compression applied to climate simulation data

Baker

Hammerling

Turton

2019

Computer Graphics Forum

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Applying lossy data compression to climate model output is an attractive means of reducing the enormous volumes of data generated by climate models. However, because lossy data compression does not exactly preserve the original data, its application to scientific data must be done judiciously. To this end, a collection of measures is being developed to evaluate various aspects of lossy compression quality on climate model output. Given the importance of data visualization to climate scientists interacting with model output, any suite of measures must include a means of assessing whether images generated from the compressed model data are noticeably different from images based on the original model data. Therefore, in this work we conduct a forced‐choice visual evaluation study with climate model data that surveyed more than one hundred participants with domain relevant expertise. In addition to the images created from unaltered climate model data, study images are generated from model data that is subjected to two different types of lossy compression approaches and multiple levels (amounts) of compression. Study participants indicate whether a visual difference can be seen, with respect to the reference image, due to lossy compression effects. We assess the relationship between the perceptual scores from the user study to a number of common (full reference) image quality assessment (IQA) measures, and use statistical models to suggest appropriate measures and thresholds for evaluating lossily compressed climate data. We find the structural similarity index (SSIM) to perform the best, and our findings indicate that the threshold required for climate model data is much higher than previous findings in the literature.

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Section: Image Quality Measuresmentioning

confidence: 99%

Evaluating image quality measures to assess the impact of lossy data compression applied to climate simulation data

Baker

Hammerling

Turton

2019

Computer Graphics Forum

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“…Similarly, being able to assess the ‘visual cost’ of a given distortion could play an important role in prosthetic design. There are already numerous metrics that can assess the perceptual quality of an image or movie based on models of the visual system (Haines and Chuang 1992, Wang et al 2004, Laparra et al 2016), but these assume no capacity for plasticity. Metrics describing the amount of ‘neurophysiologically available’ information (i.e.…”

Section: Distortions and Information Loss In Prosthetic Devicesmentioning

confidence: 99%

Learning to see again: biological constraints on cortical plasticity and the implications for sight restoration technologies

et al. 2017

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The “bionic eye” – so long a dream of the future – is finally becoming a reality with retinal prostheses available to patients in both the US and Europe. However, clinical experience with these implants has made it apparent that the vision provided by these devices differs substantially from normal sight. Consequently, the ability to learn to make use of this abnormal retinal input plays a critical role in whether or not some functional vision is successfully regained. The goal of the present review is to summarize the vast basic science literature on developmental and adult cortical plasticity with an emphasis on how this literature might relate to the field of prosthetic vision. We begin with describing the distortion and information loss likely to be experienced by visual prosthesis users. We then define cortical plasticity and perceptual learning, and describe what is known, and what is unknown, about visual plasticity across the hierarchy of brain regions involved in visual processing, and across different stages of life. We close by discussing what is known about brain plasticity in sight restoration patients and discuss biological mechanisms that might eventually be harnessed to improve visual learning in these patients.

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“…Figure 2 illustrates the components of the perceptual transform, for which we use the Normalized Laplacian Pyramid (NLP), a multi-scale nonlinear representation that mimics the operations of the retina and lateral geniculate nucleus in the human visual system. We have previously shown that distances measured between two images S x (1) Figure 2: Perceptual transform, constructed as a Normalized Laplacian Pyramid (NLP) [15]. Scene luminances S (in cd/m 2 ) are first transformed using a power function (top).…”

Section: Optimal Rendering Frameworkmentioning

confidence: 99%

Perceptually optimized image rendering

et al. 2017

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We develop a framework for rendering photographic images, taking into account display limitations, so as to optimize perceptual similarity between the rendered image and the original scene. We formulate this as a constrained optimization problem, in which we minimize a measure of perceptual dissimilarity, the Normalized Laplacian Pyramid Distance (NLPD), which mimics the early stage transformations of the human visual system. When rendering images acquired with higher dynamic range than that of the display, we find that the optimized solution boosts the contrast of low-contrast features without introducing significant artifacts, yielding results of comparable visual quality to current state-of-the art methods with no manual intervention or parameter settings. We also examine a variety of other display constraints, including limitations on minimum luminance (black point), mean luminance (as a proxy for energy consumption), and quantized luminance levels (halftoning). Finally, we show that the method may be used to enhance details and contrast of images degraded by optical scattering (e.g., fog).

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Perceptual image quality assessment using a normalized Laplacian pyramid

Cited by 135 publications

References 30 publications

Evaluating image quality measures to assess the impact of lossy data compression applied to climate simulation data

Evaluating image quality measures to assess the impact of lossy data compression applied to climate simulation data

Learning to see again: biological constraints on cortical plasticity and the implications for sight restoration technologies

Perceptually optimized image rendering

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