Blue-noise dither halftoning methods have been found to produce images with pleasing visual characteristics. Results similar to those generated with error-diffusion algorithms can be obtained using an image processing algorithm that is computationally much simpler to implement. This paper reviews and compares the various techniques that have been used to design blue-noise dither matrices. In particular, a series of visual cost function based methods, a several techniques that involve designing the dither matrices by analyzing the spatial dot distribution are discussed. Ways to extend the basic blue-noise dither techniques to multilevel and color output devices are also described, including recent advances in the design of jointly optimized color blue-noise dither matrices.
Image deblurring has been a very challenging problem in recent decades. In this article, we propose a high-quality image deblurring method with a novel image prior based on a new imaging system. The imaging system has a newly designed sensor pattern achieved by adding panchromatic (pan) pixels to the conventional Bayer pattern. Since these pan pixels are sensitive to all wavelengths of visible light, they collect a significantly higher proportion of the light striking the sensor. A new demosaicing algorithm is also proposed to restore full-resolution images from pixels on the sensor. The shutter speed of pan pixels is controllable to users. Therefore, we can produce multiple images with different exposures. When long exposure is needed under dim light, we read pan pixels twice in one shot: one with short exposure and the other with long exposure. The long-exposure image is often blurred, while the short-exposure image can be sharp and noisy. The short-exposure image plays an important role in deblurring, since it is sharp and there is no alignment problem for the one-shot image pair. For the algorithmic aspect, This work could not have been completed without support of the Kodak Research Laboratories. The work of T. Hou and H. our method runs in a two-step maximum-a-posteriori (MAP) fashion under a joint minimization of the blur kernel and the deblurred image. The algorithm exploits a combined image prior with a statistical part and a spatial part, which is powerful in ringing controls. Extensive experiments under various conditions and settings are conducted to demonstrate the performance of our method.
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