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Open Access Refining raw pixel values using a value error model to drive texture synthesis

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The goal in photography is generally the construction of a model of scene appearance. Unfortunately, statistical variations introduced by photon shot and other noise introduce errors in the raw value reported for each pixel sample. Rather than simply accepting those values as the best raw representation, the current work treats them as initial estimates of the correct values, and computes an error model for each pixel's value. The value error models for all pixels in an image are then used to drive a type of texture synthesis which refines the pixel value estimates, potentially increasing both accuracy and precision of each value. Each refined raw pixel value is synthesized from the value estimates of a plurality of pixels with overlapping error bounds and similar context within the same image. The error modeling and texture synthesis algorithms are implemented in and evaluated using KREMY (KentuckY Raw Error Modeler, pronounced "creamy"), a free software tool created for this purpose.
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Keywords: COMPUTATIONAL PHOTOGRAPHY; IMAGE ENHANCEMENT; PIXEL ERROR MODEL; RAW IMAGE; TEXTURE SYNTHESIS

Document Type: Research Article

Publication date: January 29, 2017

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  • For more than 30 years, the Electronic Imaging Symposium has been serving those in the broad community - from academia and industry - who work on imaging science and digital technologies. The breadth of the Symposium covers the entire imaging science ecosystem, from capture (sensors, camera) through image processing (image quality, color and appearance) to how we and our surrogate machines see and interpret images. Applications covered include augmented reality, autonomous vehicles, machine vision, data analysis, digital and mobile photography, security, virtual reality, and human vision. IS&T began sole sponsorship of the meeting in 2016. All papers presented at EIs 20+ conferences are open access.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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