Study On Several Key Technologies For Content-Based Multispectral Remote Sensing Image Retrieval

As large-scale, multiband earth observation data, multispectral remote sensing image(MRSI) which includes rich information of reflection and radiation that provides the finediagnostic foundation for the object discrimination and interpretation is the GIS and 3Sintegration application system's important element data. With the fast developing ofaeronautics, astronautics and sensor technology, now we could acquire plenty of real-timeearth observation data more conveniently, and widely use these data in the application ofdiverse earth objects, terrain and geology's inspection and layout. Along with sharpincrease of earth observation data's amount, the fast browse and efficient retrieval ofMRSI becomes a burdensome and tough work, which, to some extent, severely restrictsthe share and application of the RS images. The Content-Based Image Retrieval (CBIR)technology tries to implement the image data's rational organization and query retrievalcorresponding to our human being's perception habit, and supplies a new developmentdirection for the management and retrieval of MRSI. However, the spectral information ofearth objects based on the description of MRSI is ample, of great variety and also hascomplex positional relations, unclear theme content, based on these characters, the visualinformation retrieval and data organization method aimed at the MRSI has a big differencewith the content-based retrieval system used in common images and medical pictures.This paper advances a suit of effective technical scenario for the content-basedretrieval system according to the RS image's characters, advances the practical innovationin the key techniques of image autonomous segmentation, earth object character retrievaland matching, data storage model and high dimension visualization indexing. The keytechniques discussed in this paper could be widely used in the area of computer aided discrimination of RS image, earth object recognition, dynamic target tracking, disaster andtransformation surveillance and so on. The main content in this paper includes:1. Firstly, this paper systemic conclude and analyse currently CBIR research statusand mainly achievement, summarize the related key technology of CBIR technology,analyse the difference between RS image and common image, medical picture and thedifficulty bring forwarded because of this in the implementation process of CBIRtechnology, and indicate the jumping-off place of trouble shooting.2. Secondly, this paper indicate that spectral texture is important visual feature usedto distinguish the earth object according to MRSI description, and is the RS imageautonomous segmentation's most worthwhile reliant essential character of earth object.Specifically summarize and analyse currently texture feature express method andimplementation of RS image automatic segmentation which based on the multi-scalewavelet and Markov Random Field (MRF) model, then indicate the disadvantage of it. Toboth consider the spectral varying rule of interpixel and interband, we use the MRF modelto give the spectral texture description of MRSI, according to analysis of experiment result,indicate an effective MRF model spectral texture character description method. Based onthis, utilize Quad-tree image partition methodology to bring forward a method of RSimage automatic segmentation and earth object's consistency spectral texture characterextraction with the aim of retrieval, and advance a method to improve the automaticsegmentation's efficiency using principal component analysis.3. Thirdly, this paper particularly summarizes each kind of shape-based imageretrieval technology, on the basis of analyse each object shape character descriptionmethod's advantage and disadvantage, indicate that region-shape description method ismore suitable for the RS earth object than contour-shape description. Then according tothe character of RS image spectral texture automatic segmentation result and on the basisof grid shape description method, advance an adaptable method of region shape character description and comparability searching. This method has favorable scale, translation androtation invariance, and also has high character efficiency computing efficiency bigcharacter descriptor compression ratio, we use the experiment demonstrate the feasibilityof this method and the shape object's retrieval efficiency.4. Fourthly, this paper summarizes the vector space indexing machenism and metricspace indexing structure which applied to high dimension data set, through academicanalysis we indicate that the metric special indexing method is an efficient way to get ridof high-dimension data indexing's "curse of Dimensionality", and apply to the RS imagefast searching of high-dimension visual feature. Then based on the detailed analysis of PTand iDistance's indexing mechanism and suitable area, we combine this two excellentmetric special indexing method, put forward a metric special high-dimensional indexingmethod which could process space partition according to the high-dimension datadistribution feature. Then demonstrate through academic analysis and experiment that thisindexing could accomplish the distance and space direction aimed data filter operation inone query processing, and has good filtering efficiency5. Finally, according to the large-scale, magnanimity feature of RS image and thestrategy of RS image texture automatic segmentation proposed in this paper, theun-overloaded quad-tree-based blocks are used as the elements of MSRI's storagemanagement. To overcome the flaw of conditional quad-tree special indexing's large I/Otime and low query efficiency in processing large scale neighbor searching, we modify thequad-tree space indexing based on the Hilbert spce filling curve law, and then advance theHilbert space filling curve building method in allusion to the partition of un-filledquad-tree and block image data's organization strategy. The experiment proved that thiskind of data organization strategy has favorable space congregate character, and has betterdata accessing efficiency when process large scale RS image's homogeneous region dataquery. To sum up, the primary contribution and innovation in this paper are as follows:1. Firstly, a new feature descriptor of RS spectral texture is proposed which isextracted by MRF model. Based on this feature descriptor this paper further design andimplemented a RS image automatic segmentation method with the aim of retrieval.2. Secondly, a new shape feature descriptor and extraction method are proposed,which have characters of scale invariance, translation invariance and rotation invariance,and have strong antinoise ability. And the calculation of the similarity match is relativelysmall.3. Thirdly, this paper proposes a new high-dimensional indexing structure for metricspace which could sufficiently reflect the data distribution character, and could process thehigh-dimensional data's k-NN query with high efficiency, this kind of indexing could bebroadly applied to the high-dimension data set that owns the space congregate character.4. Finally, a new organization strategy of RS image based on image analysis isproposed. This paper utilize the Hilbert space filling curve character to reconstruct thequad-tree space indexing, and effectively improve the data accessing efficiency ofhomogeneous texture region and images of space neighbor earth object.In the conclusion, the successive problems and destinations are pointed out.