This paper proposes a digital image restoration algorithm for phase-coded imaging systems. In order to extend the depth-of-
field (Dof), an imaging system equipped with a properly designed phase-coded lens can achieve an approximately
constant point spread function (PSF) for a wide range of depths. In general, a phase-coded imaging system produces
blurred intermediate images and requires subsequent restoration processing to generate clear images. For low-computational
consumer applications, the kernel size of the restoration filter is a major concern. To fit for practical
applications, a pyramid-based restoration algorithm is proposed in which we decompose the intermediate image into the
form of Laplacian pyramid and perform restoration over each level individually. This approach provides the flexibility in
filter design to maintain manufacturing specification. On the other hand, image noise may seriously degrade the
performance of the restored images. To deal with this problem, we propose a Pyramid-Based Adaptive Restoration
(PBAR) method, which restores the intermediate image with an adaptive noise suppression module to improve the
performance of the phase-coded imaging system for Dof extension.
This paper proposes a novel image enhancement technique based on Gamma Map Processing (GMP). In this approach, a
base gamma map is directly generated according to the intensity image. After that, a sequence of gamma map processing
is performed to generate a channel-wise gamma map. Mapping through the estimated gamma, image details,
colorfulness, and sharpness of the original image are automatically improved. Besides, the dynamic range of the images
can be virtually expanded.
This paper presents a combinational system, which can perform the functionalities of Auto Focus (AF) and Auto Exposure (AE) at the same time in a very efficient manner. At the first step, this system uses a DOG (Difference of Gaussian) filter to measure image's contrast and sharpness simultaneously. Then, a fuzzy logic-based scheme is proposed for the adjustment of focus and exposure. This system can be easily implemented with low hardware complexity.