results for au:Farrell_J in:cs
May 31 2016 cs.CV
Many creative ideas are being proposed for image sensor designs, and these may be useful in applications ranging from consumer photography to computer vision. To understand and evaluate each new design, we must create a corresponding image processing pipeline that transforms the sensor data into a form that is appropriate for the application. The need to design and optimize these pipelines is time-consuming and costly. We explain a method that combines machine learning and image systems simulation that automates the pipeline design. The approach is based on a new way of thinking of the image processing pipeline as a large collection of local linear filters. We illustrate how the method has been used to design pipelines for novel sensor architectures in consumer photography applications.
May 16 2016 cs.CV
There is widespread interest in estimating the fluorescence properties of natural materials in an image. However, the separation between reflected and fluoresced components is difficult, because it is impossible to distinguish reflected and fluoresced photons without controlling the illuminant spectrum. We show how to jointly estimate the reflectance and fluorescence from a single set of images acquired under multiple illuminants. We present a framework based on a linear approximation to the physical equations describing image formation in terms of surface spectral reflectance and fluorescence due to multiple fluorophores. We relax the non-convex, inverse estimation problem in order to jointly estimate the reflectance and fluorescence properties in a single optimization step and we use the Alternating Direction Method of Multipliers (ADMM) approach to efficiently find a solution. We provide a software implementation of the solver for our method and prior methods. We evaluate the accuracy and reliability of the method using both simulations and experimental data. To acquire data to test the methods, we built a custom imaging system using a monochrome camera, a filter wheel with bandpass transmissive filters and a small number of light emitting diodes. We compared the system and algorithm performance with the ground truth as well as with prior methods. Our approach produces lower errors compared to earlier algorithms.