A split-plot designed experiment including four rice varieties and 10 nitrogen levels was conducted in 2003 at the Experimental Farm of Seoul National University, Suwon, Korea. Before heading, hyperspectral canopy reflectance (300-1100nm with 1.55nm step) and nine crop variables such as shoot fresh weight (SFW), leaf area index, leaf dry weight, shoot dry weight, leaf N concentration, shoot N concentration, leaf N density, shoot N density and N nutrition index were measured at 54 and 72 days after transplanting. Grain yield, total number of spikelets, number of filled spikelets and 1000-grain weight were measured at harvest. 14,635 narrow-band NDVIs as combinations of reflectances at wavelength ~lambdal~;and~;~lambda2 were correlated to the nine crop variables. One NDVI with the highest correlation coefficient with a given crop variable was selected as the NDVI of the best fit for this crop variable. As expected, models to predict crop variables before heading using the NDVI of the best fit had higher r2 (>10~%) than those using common broad- band NDVI red or NDVI green. The models with the narrow-band NDVI of the best fit overcame broad- band NDVI saturation at high LAI values as frequently reported. Models using NDVIs of the best fit at booting showed higher predictive capacity for yield and yield component than models using crop variables.

A quick and automatic detection with no harm to the goods is very important task for improving quality control, process control and labour reduction. In real fields of industry, defect detection is mostly accomplished by skillful workers. A narrow band eliminating spatial filter having characteristics of removing the specified spatial frequency is developed by the author, and it is proved that the filter has an excellent ability for on-line and real time detection of surface defect. By the way,. this spatial filter shows a ripple phenominum in filtering characteristics. So, it is necessary to remove the ripple component for the improvement of filter gain, moreover efficiency of defect detection. The spatial filtering method has a remarkable feature which means that it is able to set up weighting function for its own sake, and which can to obtain the best signal relating to the purpose of the measurement. Hence, having an eye on such feature, theoretical analysis is carried out at first for optimal design of narrow band eliminating spatial filter, and secondly, on the basis of above results spatial filter is manufactured, and finally advanced effectiveness of spatial filter is evaluated experimentally.

The defects occurred in knitted fabrics have several types due to some trouble sources. In particular, the defects caused by knitting machine troubles give a serious damage to the whole webs. It is, therefore, necessary to discriminate the kind of defects. The method to discriminate the type and size of defects has been proposed, which is used a pair of narrow band eliminating spatial filters. This method is based upon an isotropic signal processing in time domain. This paper is to confirm that the proposed method can be useful in the discrimination of defects, having analyzed in spatial frequency domain.