The traceability of egg quality is related to the safety of the egg food, the traditional identification method is to use the egg quality parameters, and the operation process is too complicated. Hyperspectral characteristics reflect material properties, and each material has its own spectral characteristic curve, which is a very important feature for material classification and identification. In this paper, the spectral characteristic data of eggs was obtained by the spectrometers and the hyperspectral imaging instrument, respectively. After processing and analyzing, a nondestructive testing method of egg quality based on hyperspectral characteristics was proposed. The testing results are analyzed in depth, and some very useful conclusions are obtained.
Synthetic aperture radar (SAR) image change detection is a very complex problem like SAR imaging mechanism. Every
change detection method has its advantage and disadvantage and there are no optimal change detection approaches. If
general methods directly perform SAR image change detection, it can not obtain the satisfied results. Sometimes, for a
pair of multi-temporal SAR images, different detection methods can obtain different detected results; what's more, the
results are contrary. In order to improve SAR image change detection precision, this paper studies SAR image change
mechanism in detail and represents the change types of SAR images. The new integrative change detection algorithm is
proposed, and the real SAR image data tests the methods.
The detection of faint, small and hidden targets in synthetic aperture radar (SAR) image is still
an issue for automatic target recognition (ATR) system. How to effectively separate these targets from the
complex background is the aim of this paper. Independent component analysis (ICA) theory can enhance
SAR image targets and improve signal clutter ratio (SCR), which benefits to detect and recognize faint
targets. Therefore, this paper proposes a new SAR image target detection algorithm based on ICA. In
experimental process, the fast ICA (FICA) algorithm is utilized. Finally, some real SAR image data is used to
test the method. The experimental results verify that the algorithm is feasible, and it can improve the SCR of
SAR image and increase the detection rate for the faint small targets.