KEYWORDS: Image fusion, Denoising, Image contrast enhancement, Image filtering, Image enhancement, Digital filtering, Image processing, Gaussian filters, Human vision and color perception, RGB color model
When the scene reached the human eye or other sensor through the underwater medium, the original color property of the object could be basically lost, and the background of most images was blue-green. In this paper, to remove the blue-green color of the underwater image and increase the color contrast of the image, a novel fusion method of two images was proposed. The two images were derived from the filtering denoising result and the contrast enhancement result after whitebalancing version of the original degraded image. Then, based on the two images, the associated weight maps were designed to enhance edge texture and color contrast of the output image. Finally, to avoid artifacts in the reconstructed image, we adopted the multiscale fusion strategy to fuse the processed two images. Experiments showed that our algorithm achieved better image contrast and edge sharpness than other methods and obtained better exposure for darker areas of the image.
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.
In recent years, the incidence of congenital malformations was increasing obviously due to the significant increase in the number of women with advanced maternal age after the implementation of two children policy in China. Traditional prenatal testing methods faced the problems of the high risk of miscarriage, low sensitivity, and time-consuming. Development of a novel method with the features of noninvasive, rapid, cost-effective and high sensitivity will be of vital clinical value for prenatal testing. This review provided an overview of the common birth defects and compared the merits and drawbacks among current most-used prenatal detection methods. The characteristics of spectroscopic technologies, as well as their applications in prenatal testing were summarized. Spectral karyotyping, real-time fluorescence quantitative PCR, SNP allele site analysis, etc. using fluorescence spectrum analysis method and Raman spectroscopy have been reported in the application of prenatal testing. Finally, a new idea by taking the advantages of SERS for Down syndrome detection in pregnant woman blood was proposed, which may be providing a promising approach for realizing rapid, sensitive and noninvasive prenatal testing.
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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