Perceptual image quality assessment using a normalized Laplacian pyramid

Valero Laparra; Johannes Balle; Alexander Berardino; Eero P. Simoncelii

doi:10.2352/ISSN.2470-1173.2016.16HVEI-103

Perceptual image quality assessment using a normalized Laplacian pyramid

Valero Laparra, Johannes Balle, Alexander Berardino, Eero P. Simoncelii

Neural Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We present an image quality metric based on the transformations associated with the early visual system: local luminance subtraction and local gain control. Images are decomposed using a Laplacian pyramid, which subtracts a local estimate of the mean luminance at multiple scales. Each pyramid coefficient is then divided by a local estimate of amplitude (weighted sum of absolute values of neighbors), where the weights are optimized for prediction of amplitude using (undistorted) images from a separate database. We define the quality of a distorted image, relative to its undistorted original, as the root mean squared error in this "normalized Laplacian " domain. We show that both luminance subtraction and amplitude division stages lead to significant reductions in redundancy relative to the original image pixels. We also show that the resulting quality metric provides a better account of human perceptual judgements than either MS-SSIM or a recently-published gain-control metric based on oriented filters.

Original language	English (US)
Title of host publication	Human Vision and Electronic Imaging 2016, HVEI 2016
Editors	Thrasyvoulos N. Pappas, Huib de Ridder, Bernice E. Rogowitz
Publisher	Society for Imaging Science and Technology
Pages	43-48
Number of pages	6
ISBN (Electronic)	9781510827943
DOIs	https://doi.org/10.2352/ISSN.2470-1173.2016.16HVEI-103
State	Published - 2016
Event	Human Vision and Electronic Imaging 2016, HVEI 2016 - San Francisco, United States Duration: Feb 14 2016 → Feb 18 2016

Publication series

Name	Human Vision and Electronic Imaging 2016, HVEI 2016

Conference

Conference	Human Vision and Electronic Imaging 2016, HVEI 2016
Country/Territory	United States
City	San Francisco
Period	2/14/16 → 2/18/16

ASJC Scopus subject areas

Atomic and Molecular Physics, and Optics
Electrical and Electronic Engineering
Computer Science Applications

Access to Document

10.2352/ISSN.2470-1173.2016.16HVEI-103

Cite this

Laparra, V., Balle, J., Berardino, A., & Simoncelii, E. P. (2016). Perceptual image quality assessment using a normalized Laplacian pyramid. In T. N. Pappas, H. de Ridder, & B. E. Rogowitz (Eds.), Human Vision and Electronic Imaging 2016, HVEI 2016 (pp. 43-48). (Human Vision and Electronic Imaging 2016, HVEI 2016). Society for Imaging Science and Technology. https://doi.org/10.2352/ISSN.2470-1173.2016.16HVEI-103

Perceptual image quality assessment using a normalized Laplacian pyramid. / Laparra, Valero; Balle, Johannes; Berardino, Alexander et al.
Human Vision and Electronic Imaging 2016, HVEI 2016. ed. / Thrasyvoulos N. Pappas; Huib de Ridder; Bernice E. Rogowitz. Society for Imaging Science and Technology, 2016. p. 43-48 (Human Vision and Electronic Imaging 2016, HVEI 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Laparra, V, Balle, J, Berardino, A & Simoncelii, EP 2016, Perceptual image quality assessment using a normalized Laplacian pyramid. in TN Pappas, H de Ridder & BE Rogowitz (eds), Human Vision and Electronic Imaging 2016, HVEI 2016. Human Vision and Electronic Imaging 2016, HVEI 2016, Society for Imaging Science and Technology, pp. 43-48, Human Vision and Electronic Imaging 2016, HVEI 2016, San Francisco, United States, 2/14/16. https://doi.org/10.2352/ISSN.2470-1173.2016.16HVEI-103

Laparra V, Balle J, Berardino A, Simoncelii EP. Perceptual image quality assessment using a normalized Laplacian pyramid. In Pappas TN, de Ridder H, Rogowitz BE, editors, Human Vision and Electronic Imaging 2016, HVEI 2016. Society for Imaging Science and Technology. 2016. p. 43-48. (Human Vision and Electronic Imaging 2016, HVEI 2016). doi: 10.2352/ISSN.2470-1173.2016.16HVEI-103

Laparra, Valero ; Balle, Johannes ; Berardino, Alexander et al. / Perceptual image quality assessment using a normalized Laplacian pyramid. Human Vision and Electronic Imaging 2016, HVEI 2016. editor / Thrasyvoulos N. Pappas ; Huib de Ridder ; Bernice E. Rogowitz. Society for Imaging Science and Technology, 2016. pp. 43-48 (Human Vision and Electronic Imaging 2016, HVEI 2016).

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title = "Perceptual image quality assessment using a normalized Laplacian pyramid",

abstract = "We present an image quality metric based on the transformations associated with the early visual system: local luminance subtraction and local gain control. Images are decomposed using a Laplacian pyramid, which subtracts a local estimate of the mean luminance at multiple scales. Each pyramid coefficient is then divided by a local estimate of amplitude (weighted sum of absolute values of neighbors), where the weights are optimized for prediction of amplitude using (undistorted) images from a separate database. We define the quality of a distorted image, relative to its undistorted original, as the root mean squared error in this {"}normalized Laplacian {"} domain. We show that both luminance subtraction and amplitude division stages lead to significant reductions in redundancy relative to the original image pixels. We also show that the resulting quality metric provides a better account of human perceptual judgements than either MS-SSIM or a recently-published gain-control metric based on oriented filters.",

author = "Valero Laparra and Johannes Balle and Alexander Berardino and Simoncelii, {Eero P.}",

note = "Funding Information: This work was supported by the Howard Hughes Medical Institute, and the APOSTD/2Q14/095 Generalitat Valenciana grant (Spain).; Human Vision and Electronic Imaging 2016, HVEI 2016 ; Conference date: 14-02-2016 Through 18-02-2016",

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doi = "10.2352/ISSN.2470-1173.2016.16HVEI-103",

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AU - Balle, Johannes

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N2 - We present an image quality metric based on the transformations associated with the early visual system: local luminance subtraction and local gain control. Images are decomposed using a Laplacian pyramid, which subtracts a local estimate of the mean luminance at multiple scales. Each pyramid coefficient is then divided by a local estimate of amplitude (weighted sum of absolute values of neighbors), where the weights are optimized for prediction of amplitude using (undistorted) images from a separate database. We define the quality of a distorted image, relative to its undistorted original, as the root mean squared error in this "normalized Laplacian " domain. We show that both luminance subtraction and amplitude division stages lead to significant reductions in redundancy relative to the original image pixels. We also show that the resulting quality metric provides a better account of human perceptual judgements than either MS-SSIM or a recently-published gain-control metric based on oriented filters.

AB - We present an image quality metric based on the transformations associated with the early visual system: local luminance subtraction and local gain control. Images are decomposed using a Laplacian pyramid, which subtracts a local estimate of the mean luminance at multiple scales. Each pyramid coefficient is then divided by a local estimate of amplitude (weighted sum of absolute values of neighbors), where the weights are optimized for prediction of amplitude using (undistorted) images from a separate database. We define the quality of a distorted image, relative to its undistorted original, as the root mean squared error in this "normalized Laplacian " domain. We show that both luminance subtraction and amplitude division stages lead to significant reductions in redundancy relative to the original image pixels. We also show that the resulting quality metric provides a better account of human perceptual judgements than either MS-SSIM or a recently-published gain-control metric based on oriented filters.

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Perceptual image quality assessment using a normalized Laplacian pyramid

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