Purdue Research Foundation

Nicholas Chimitt

Stanley Chan

Zhiyuan Mao

An image generator engine for generating distorted images from an input image is disclosed which includes a random seed generator adapted to generate random seeds, a model adapted to receive the random seeds and generate a first plurality of sets of Zernike coefficients (FPSZC), a pixel shifter adapted to shift pixels of the input image, a phase to space (P2S) transformer adapted to in parallel receive the FPSZC and generate a predetermined number of P2S coefficients, a learned basis function generator adapted to generate learned basis function matrices, a convolver adapted to convolve each pixel of the tilted image by the learned basis functions thereby generating a plurality of convolved pixels, and a blurrer adapted to receive the plurality of the convolved pixels and multiply by the corresponding P2S coefficients and apply a summation to generate the distorted image.

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West Lafayette, IN, United States of America

Nicholas Chimitt