Mr. Kedarnath P. Vilankar Profile

Kedarnath P. Vilankar

at Oklahoma State Univ

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Proceedings Article | 14 March 2013 Paper

A database of local masking thresholds in natural images

Md Mushfiqul Alam, Kedarnath Vilankar, Damon Chandler

Proceedings Volume 8651, 86510G (2013) https://doi.org/10.1117/12.2008581

KEYWORDS: Target detection, Spatial frequencies, Databases, Bridges, Data modeling, Performance modeling, Quantization, Detection and tracking algorithms, Visualization, Wavelets

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The ability of an image region to hide or mask a target signal continues to play a key role in the design of numerous image-processing and vision applications. However, one of the challenges in designing an effective model of masking for natural images is the lack of ground-truth data. To address this issue, this paper describes a psychophysical study designed to obtain local contrast detection thresholds (masking maps) for a database of natural images. Via a three-alternative forced-choice experiment, we measured the thresholds for detecting 3.7 cycles/deg vertically oriented log-Gabor targets placed within each 85×85-pixel patch (1.9 deg patch) of 15 natural images from the CSIQ image database [Larson and Chandler, JEI, 2010]. Thus, for each image, we obtained a masking map in which each entry in the map denotes the RMS contrast threshold for detecting the log-Gabor target at the corresponding spatial location in the image. Here, we describe the psychophysical procedures used to collect the thresholds, we provide analyses of the results, and we provide some outcomes of predicting the thresholds via basic low-level features, a computational masking model, and two modern imagequality assessment algorithms.

Proceedings Article | 3 February 2011 Paper

On the perception of band-limited phase distortion in natural scenes

Kedarnath Vilankar, Logesh Vasu, Damon Chandler

Proceedings Volume 7865, 78650C (2011) https://doi.org/10.1117/12.872657

KEYWORDS: Spatial frequencies, Wavelets, Distortion, Image quality, Visualization, Wavelet transforms, Visual system, Image visualization, Analytical research, Continuous wavelet transforms

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It is widely believed that the phase spectrum of an image contributes much more to the image's visual appearance than the magnitude spectrum. Several researchers have also shown that this phase information can be computed indirectly from local magnitude information, a theory which is consistent with the physiological evidence that complex cells respond to local magnitude (and are insensitive to local phase). Recent studies have shown that tasks such as image recognition and categorization can be performed using only local magnitude information. These findings suggest that the human visual system (HVS) uses local magnitude to infer global phase (image-wide phase spectrum) and thereby determine the image's appearance. However, from a signal-processing perspective, both local magnitude and local phase are related to global phase. Moreover, in terms of image quality, distorting the local phase can result in a severely degraded image. These latter facts suggest that the HVS uses both local magnitude and local phase to determine an image's appearance. We conducted an experiment to quantify the contributions of local magnitude and local phase toward image appearance as a function of spatial frequency. Hybrid images were created via a complex wavelet transform in which the the low frequency magnitude, low frequency phase, high frequency magnitude, and high frequency phase were taken from 2-4 different images. Subjects were then asked to rate how much each of the 2-4 images contributed to the the appearance of the hybrid image. We found that local magnitude is indeed an important factor for image appearance; however, local phase can play an equally important role, and in some cases, local phase can dominate the image's appearance. We discuss the implication of these results in terms of image quality and visual coding.

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