Color filter array recovery using a threshold-based variable number of gradients

The increase in the popularity of digital cameras over the past few years has provided motivation to improve all elements of the digital photography signal chain. As a contribution towards this common goal, we present a new CFA recovery algorithm, which recovers full-color images from single-detector digital color cameras more accurately than previously published techniques. This CFA recovery algorithm uses a threshold-based variable number of gradients. In order to recover missing color information at each pixel, we measure the gradient in eight directions based on a 5 X 5 neighborhood surrounding that pixel. Each gradient value is defined as a linear combination of the absolute differences of the like-colored pixels in this neighborhood. We then consider the entire set of eight gradients to determine a threshold of acceptable gradients. For all of the gradients that pass the threshold test, we use color components from the corresponding areas of the 5 X 5 neighborhoods to determine the missing color values. We test our CFA recovery algorithm against bilinear interpolation and a single- gradient method. Using a set of standard test images, we show that our CFA recovery algorithm reduces the MSE by over 50 percent compared to conventional color recovery algorithms. In addition, the resolution test we developed also show that the new CFA recovery algorithm increases the resolution by over 15 percent. The subjective qualities of test images recovered using the new algorithm also show noticeable improvement.