A water wake detection method of airphotoes is proposed based on two-dimensional principal component analysis
(2DPCA) of the polar Fourier spectrum. This method improves the traditional Principal Components Analysis to obtain
the image direction from its Fourier power spectrum, transforms the Fourier spectrum to the polar coordinate based on
the image direction, so the polar Fourier spectrum is translation and rotation invariant. Compared to the previous method
of partitioning the Fourier spectrum to achieve texture features, the row 2DPCA, the column 2DPCA and the improved
2DPCA are used to analysis the polar Fourier spectrum. From experiment results of 40 images, it is proved that the
proposed algorithm can fetch the wake texture precisely.
Field investigation was carried out during 4, April, 2001 to 15, April, 2001 around Zhoushan Fishing Ground. The surface nutrient and suspended sediment (SS) concentration exhibit remarkable features. Most striking are that all data show very high values at the end member Changjiang Diluted Water (CDW), decrease abruptly at the onset of mixing of Taiwan Warm Current. The frontal zone is mainly located near 123°E, which is supported powerfully by NOAA sea surface temperature (SST) image. Total phosphorus (TP) concentration is affected profoundly with SS concentration, for robust relationship between total particulate (TPP) and TP is observed in most stations (R2=0.9073, n=10). Positive correlation between in-situ concentration of TP and SS are found. The experimental regression equation is represented as CTP=0.0195*CSS+0.5266, R2=0.5645(n=32). NO3- is the main form of DIN, of more than 82% in DIN, exhibits considerable conservative feature. Although lack of in-situ CDOM measurement, good relationship was established between in-situ DIN concentration with near real time SeaWiFS ACD data: CDIN=135.1351*CACD-6.0, R2=0.7514 (n=15). The two empirical regression algorithms were utilized for inversing TP and DIN concentration from SeaWiFS SS and ACD. The algorithms were adopted to evaluate the impaction of terrestrial pollutant input to the area by CDW.
A simple and fast multi-channel filtering algorithm is presented in the paper for texture segmentation. This algorithm requires only a small number of channels and automatically determines the channel parameters by analysis of the Fourier power spectrum. Also it does not need a priori knowledge about the type and number of textures occurring in the input images. We can gain categories number by the square-error plot of different clusters. It does not involve any human intervention. The algorithm is tested extensively with a variety of Brodatz's textures and real textures. The segmentation results validate the practicability of this algorithm.
As one of important applications in Synthetic Aperture Radar (SAR) images, the recognition of urban area has received considerable attentions in remote sensing. The extraction of line segment is very critical technology to recognize the urban area because many objects such as streets and buildings are line segment. The common method to extract line segment is Hough transform, but most of the previous methods are based on binary images. So we have to select a threshold to binarizate the image, but at most time we can not determine the threshold properly, resulting in the lost of useful information. To solve the problem, an improved Hough transform algorithm on gray level, which can make the extraction of line segment independent of the noise and the length of line segment, is proposed. The approach is validated by the analysis of SAR images.