Literature DB >> 16403546

Local luminance and contrast in natural images.

Robert A Frazor1, Wilson S Geisler.   

Abstract

Within natural images there is substantial spatial variation in both local contrast and local luminance. Understanding the statistics of these variations is important for understanding the dynamics of receptive field stimulation that occur under natural viewing conditions and for understanding the requirements for effective luminance and contrast gain control. Local luminance and contrast were measured in a large set of calibrated 12-bit gray-scale natural images, for a number of analysis patch sizes. For each image and patch size we measured the range of contrast, the range of luminance, the correlation in contrast and luminance as a function of the distance between patches, and the correlation between contrast and luminance within patches. The same analyses were also performed on hand segmented regions containing only "sky", "ground", "foliage", or "backlit foliage". Within the typical image, the 95% range (2.5-97.5 percentile) for both local luminance and local contrast is somewhat greater than a factor of 10. The correlation in contrast and the correlation in luminance diminish rapidly with distance, and the typical correlation between luminance and contrast within patches is small (e.g., -0.2 compared to -0.8 for 1/f noise). We show that eye movements are frequently large enough that there will be little correlation in the contrast or luminance on a receptive field from one fixation to the next, and thus rapid contrast and luminance gain control are essential. The low correlation between local luminance and contrast implies that efficient contrast gain control mechanisms can operate largely independently of luminance gain control mechanisms.

Mesh:

Year:  2006        PMID: 16403546     DOI: 10.1016/j.visres.2005.06.038

Source DB:  PubMed          Journal:  Vision Res        ISSN: 0042-6989            Impact factor:   1.886


  55 in total

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8.  Modeling lateral geniculate nucleus response with contrast gain control. Part 1: formulation.

Authors:  Davis Cope; Barbara Blakeslee; Mark E McCourt
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9.  An analysis of visual masking, with a defense of 'Stopped Processing'.

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10.  Knowledge-Driven Contrast Gain Control is Characterized by Two Distinct Electrocortical Markers.

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