Terahertz composite imaging method

In order to improve the imaging quality of terahertz(THz) spectroscopy, Terahertz Composite Imaging Method(TCIM) is proposed. The traditional methods of improving THz spectroscopy image quality are mainly from the aspects of de-noising and image enhancement. TCIM breaks through this limitation. A set of images, reconstructed in a single data collection, can be utilized to construct two kinds of composite images. One algorithm, called Function Superposition Imaging Algorithm(FSIA), is to construct a new gray image utilizing multiple gray images through a certain function. The features of the Region Of Interest(ROI) are more obvious after operating, and it has capability of merging ROIs in multiple images. The other, called Multi-characteristics Pseudo-color Imaging Algorithm(Mc Pc IA), is to construct a pseudo-color image by combining multiple reconstructed gray images in a single data collection. The features of ROI are enhanced by color differences. Two algorithms can not only improve the contrast of ROIs, but also increase the amount of information resulting in analysis convenience. The experimental results show that TCIM is a simple and effective tool for THz spectroscopy image analysis.

External defects and severity level evaluation of potato using single and multispectral imaging in near infrared region Author links open overlay panel

Non-invasive potato defects detection has been demanded for sorting and grading purpose.Researches on the classification of the defects has been available,however,investigation on the severity level calculation is limited.For the detection of the common scab,it has been found that imaging in the infrared region provide an interesting characteristic that could distinguish defected area to normal area.Thus,investigations on this wavelength range is interesting to add more knowledge and for applications.In this research,the multispectral image has been obtained and investigated especially at three wavelengths(950,1150,1600 nm).Image pre-processing and pseudo-color conversion techniques were explored to enhance the contrast between defects,normal background skin area and soil deposits.Results show that external defects,such as common scab and some mechanical damage types,appear brighter in the near infrared region,especially at 1600 nm against the normal skin background.It has been found that pseudo-color images conversion provides more information regarding type if surface characteristics compared to grayscale single imaging.Image segmentation using pseudo-color images after multiplication operation pre-processing could be used for common scab and mechanical damage detection excluding soil deposits with a Dice Sorensen coefficient of 0.64.In addition,image segmentation using single image at 1600 nm shown relatively better results with Dice Sorensen coefficient of 0.72 with note that thick soil deposits will also be segmented.Defect severity level evaluation had an R2 correlation of 0.84 against standard measurements of severity.

Fusion of urban remote image based on multi-characteristics

A fusion approach is proposed to refine the resolution of urban multi-spectral images using the corresponding high-resolution panchromatic （PAN） images. Firstly, the two images are decomposed by wavelet transformation, and five texture features are extracted from high-frequency detailed sub-images. Then a multi-characteristics fusion rule is used to merge wavelet coefficients from the two images according to the extracted features. Experimental results indicate that, comparing with the non-characteristic methods, the proposed method can efficiently preserve the spectral information while improving the spatial resolution of the urban remote sensing images.