The performance of coded exposure photography-based image deblurring highly depends on its coded pattern to use. Conventionally, the length of the coded pattern has been optimized under the assumption that its length is equal to the length of motion blur. However, coded patterns of different lengths from the same motion blur may have better invertibility than the conventional patterns. In this paper, we investigate a method to optimize the coded pattern within an extended range of length candidates. We demonstrate the effectiveness of the proposed method using a real dataset.
Motion blur is easily observable in an image having moving objects, and the coded exposure photography is one of the well-known solutions to its removal. In this paper, we propose a novel coded exposure photography technique to capture images of moving objects using coded flashes. Noting that the camera acquires a multi-channel image at once by using a color filter array, we modulate each channel image differently by using multi-band coded flashes. By modulating the point spread function of the acquired channel image to have a jointly invertible point spread function, its deconvolution performance is significantly improved compared to the existing single image coded exposure photography. We prove the effectiveness of the proposed method through experiments using synthetic and real data.
Motion blurs inevitably occur in an image photographing fast moving objects, and its removal, known as motion deblurring, is one of the most well-known ill-posed problems. In this paper, we investigate the deblurring problem of motion blurs by using a modulated external light. Noting that the motion blurs depend both on ambient light and modulated external light, we investigate how to design a motion deblurring method considering not only the external light but also the ambient light. The deblurring performance of the proposed method is compared to that by the conventional method which only considers the external modulated light.
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