This paper proposes a novel method for modeling retinal cone distribution in humans. It is based on Blue-noise sampling algorithms being strongly related with the mosaic sampling performed by cone photoreceptors in the human retina. Here we present the method together with a series of examples of various real retinal patches. The same samples have also been created with alternative algorithms and compared with plots of the center of the inner segments of cone photoreceptors from imaged retinas. Results are evaluated with different distance measure used in the field, like nearest-neighbor analysis and pair correlation function. The proposed method can effectively describe features of a human retinal cone distribution by allowing to create samples similar to the available data. For this reason, we believe that the proposed algorithm may be a promising solution when modeling local patches of retina.
Optical systems in digital cameras present a limit during the acquisition of standard and High Dynamic Range Images (HDRI) due to the presence of veiling glare, an artifact caused by an unwanted spread of the source of light. In this paper, we analyze the state-of-the-art of veiling glare removal in HDRI, giving attention to the paper presented by Talvala. Then we describe an algorithm for veiling glare removal based on the same occlusion mask, to study the benefits provided by it in HDRI acquisition process. Finally, we demonstrate the efficiency of the occlusion mask method in veiling glare removal without any post production estimation and subtraction.
The Random spray Retinex (RSR) algorithm was developed by taking into consideration the mathematical description of Milano-Retinex. The RSR substituted random paths with random sprays. Mimicking some characteristics of the human visual system (HVS), this article
proposes two variants of RSR adding a mechanism of region of interest (ROI). In the first proposed model, a cone distribution based on anatomical data is considered as ROI. In the second model, the visual resolution depending on the visual field based on the knowledge of visual information
processing is considered as ROI. We have measured actual eye movements using an eye-tracking system. By using the eye-tracking data, we have simulated the HVS using test images. Results show an interesting qualitative computation of the appearance of the processed area around real gaze points.
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