Due to the vagueness of mobile video shooting at night, the blurry low-light images obtained from it hindered humans from acquiring visual information and computer vision algorithms. In this paper, to lower color and lightness distortion when increasing visibility, a novel brightness mapping function based on the camera mapping model was proposed by using the chi-squared distribution. Then, the well-exposed images were obtained by using the brightness evaluation technique and the brightness mapping function. Finally, an existing image deblurring algorithm based on convolution and dark channel was employed to help deblur well-exposed images. Experiments showed that our method could achieve accurate contrast and lightness enhancement than several state-of-the-art methods and obtain decent sharp well-exposed images.
KEYWORDS: Video, Signal processing, Cameras, Video processing, Sensors, Digital electronics, Analog electronics, Motion models, Data modeling, Visualization
Traditional sensors and systems for wrist pulse acquisition, known as inconvenient, contact, depends on the digital and analog circuits. In this paper, a method in video motion processing at one-demensional signal extraction and analysis is proposed. It can be applied for wrist pulse acquisition and based on subtle video motion amplification algorithm. This is the demostraction of a low-cost (only need ordinary camera on the cell phone), accurate method for cantact-free wrist pulse acquiring that is capable of performing measurements in different illumination conditions. As the ultimate recovered single and all periodic pulse signal shown, it can be demonstracted that the proposed method can get accurate pulse signal compared to traditional methods.
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