Image Mosaic Technique Based On Invariant Feature And Hard-disk Direct Writing Recording Technique Based On Soft Synchronization

Remote sensing image mosaic and recording technique is a key technique usedin the field of information-based reconnaissance equipment research anddevelopment to obtain high-resolution and large-scale battlefield images. It includesimage mosaic technique based on invariant feature and hard-disk direct writingrecording technique based on soft synchronization. However, the existing imagemosaic methods have such weak points as poor stability and adaptability, lowrecording speed, not highly automated operation, and very complicated structureand excessively high dimensions of feature descriptors. And none of the existingrecording techniques has a high enough continuous recording rate, which has adirect influence on further improvement of remote sensing reconnaissanceperformance. Therefore, this thesis intends to study fully automatic mosaic andreal-time continuous recording technique for images obtained using high resolutionimaging sensors, and to formulate a fully automatic mosaic technique for large scaleremote sensing images, and to find a high-speed recording system with a longcontinuous recording time suitable for reliable operation under asperityenvironments, thereby providing theoretical and technical bases for furtherimprovement of China’s remote reconnaissance system performance. This researchalso benefits space exploration, space remote sensing data processing, radarimaging data processing, radar imaging data processing and anti-SAR.This thesis starts with a summary presentation of the basic structure of aremote sensing image mosaic system, and the derivation of image transportmathematic model based on the basic principle of optical imaging, and a systematicexposition of key techniques, such as matching, transform, correction and fusion ofimages used for large scale image mosaic.Scale invariant feature transform (SIFT) is introduced though the in-depthstudy of conventional image feature extraction techniques for the extraction of largescale remote sensing image features. In light of the imperfect invariance andexcessively high dimensions of SIFT descriptors, a new way of constructing SIFTdescriptors based on sectorial segmentation is proposed to avoid the rotationaloperation during the construction of descriptor, and the number of dimensions is reduced from128to48while the invariance of descriptor is holden. In light of thepoor adaptability of SIFT descriptor with respect to an image with low contrast, aself-adaptive contrast threshold is proposed for the extraction of key points, therebyenhancing the adaptability of SIFT algorithm to a remote sensing image, i.e.expanding its scope of applicability.In light of the large numbers of SIFT features and large-scale remote sensingimages, three automatic matching strategies based on statistics, transform modeland improved RANSAC are proposed for the automatic calculation of thresholdsneeded for input images in the matching process. A fast automatic remote sensingimage mosaic process is proposed so that the optimization matching coordinate canbe transferred immediately after feature extraction in the sub-sampled images andparameter optimization to the original images for matching and mosaic, and theconventional mosaic seams are eliminated in the process as well. The new methodreduces the processing time and increases the automation level of remote sensingimage mosaic.In order to solve the conflict between the low recording speed of aconventional recording system and the high continuous transfer speed of image data,a hard-disk high-speed direct rating recording method based on multi-channel softsynchronization is proposed through a comparative study of different large capacitydata recording systems. The self-starting speed and the continuous recording speedof hard-disks are effectively increased by re-designing the self-startingsynchronization direct writing controller and optimizing the recording sequence ofSCSI hard-disks. A technical support is thus provided for the realization of real-timerecording of remote sensing image data at200MB/s.With programs developed and equipment produced, experiments are made withfeature descriptors, made in a new way automatic matching strategies, a large-scaleremote sensing image mosaic model, and the multi-channel soft synchronizationhigh-speed data recording system proposed in this thesis for performance evaluation.Experimental results indicate that the overall matching time has been improvedobviously by using the feature descriptors proposed while the matchingperformance is equivalent to that of original SIFT algorithm; the self-adaptivecontrast threshold control method has been used to effectively improve theadaptability of feature extraction algorithm to remote sensing images, and to make the distribution of feature points extracted even; the automatic matching strategybased on improved RANSAC has a stable performance, and the average reeall ratioof experimental images used goes up to98.3%; the quality of fused images realizedusing large scale remote sensing image mosaic method satisfied the actual needs,the transition between mosaic regions is smooth, and the stitching time is greatlyreduced. The multi-channel soft synchronization high-speed recording techniqueproposed in this thesis is used to realize the real-time nondestructive recording oflarge scale remote sensing images at200MB/s, more than double the speed ofsimilar recording systems, and it is small in size, easy to use, and has very goodexpandability as well.