With the development of miniaturization of drones and spectral cameras, unmanned Airborne spectral imaging technology has become possible. How to reduce the volume and quality of multi-spectral cameras while improving data acquisition performance and efficiency, making them more widely used in low-altitude remote sensing has become the focus of current research. In this paper, we develop multi-spectral camera development and data preprocessing technology based on array filter splitting. In the development of camera, we replace the optical path splitting, filter wheel and multi-lens splitting by filter splitting, which solves the multi-spectral camera. At the same time of data quality, two array filters were designed because the imaging method limited the camera to the ideal volume and quality. The improved filter greatly reduced the spectral aliasing between the bands. In the data processing, an improved SURF stitching algorithm based on sparse matrix beam adjustment is proposed to improve the speed of image stitching. The research results show that this paper successfully developed a multi-spectral camera with simple optical path, high acquisition efficiency, stable performance, small mass and low cost, and successfully combined with small and small drones for data acquisition and processing. The academic value and production value, the data acquisition achieves the generation of multi-spectral image of the whole scene, and the band stitching precision is 0.12 pixels, which has high application value.
Axis-shift multi-camera has been gradually applied in the aerial photogrammetry because of its advantages on structure design. In this paper, the basic axis-shift theory is analyzed, and an improved calibration method is described. A prototype system, including two axis-shift cameras, is developed to validate the feasibility and correctness of the proposed method. With the help of a high-precision indoor control field, the parameters of single camera and the relative orientation parameters of the dual camera system are calculated respectively. Experiment result indicates that this calibration method is suitable for the axis-shift multi camera system.
The application of high-resolution airborne images becomes more and more extensive. However because of the complexity of atmospheric environment, airborne remote sensing imaging process is easily affected by cloud and mist, which results in airborne image blurred or loss of information. So it is a necessary task to remove effects of cloud to get clearer images before the next application such as image registration. This paper proposes a new method of removing thin cloud cover from single airborne image. This method applies scale space transform to get scale space sequence images. Then we use difference between different levels to extract cloud area. Next, we use gray classification which represents cloud effect degree in the highest level of cloud area. Finally, we use the original image filtered by Laplacian to subtract the last step result. Compared with other thin cloud cover removal methods which include the homomorphic filtering method, wavelet transform method and mathematical morphology by visual evaluation and statistical analysis, the method proposed by this paper proves to be the most efficient way in the processing of thin cloud cover of airborne image.
According to the characteristic of multi-digital cameras system, the paper presents the concept of System's Interior
Orientation Parameters (SIOP) and verifies that the SIOP acquired from calibration in the inside field can effectively
improve the accuracy and efficiency of data processing of multi-digital cameras system. Importantly, the paper builds a
solution model of SIOP and verifies the feasibility of this solution model by experiment. Above all, the major research in
the paper gives an answer to the question that how to calibrate the multi-digital cameras system efficiently and
Several composite camera systems were made for wide coverage by using 3 or 4 oblique cameras. A virtual projecting
center and image was used for geometrical correction and mosaic with different projecting angles and different spatial
resolutions caused by oblique cameras. An imaging method based axis-shift theory is proposed to acquire wide coverage
images by several upright cameras. Four upright camera lenses have the same wide angle of view. The optic axis of lens
is not on the center of CCD, and each CCD in each camera covers only one part of the whole focus plane. Oblique
deformation caused by oblique camera would be avoided by this axis-shift imaging method. The principle and
parameters are given and discussed. A prototype camera system is constructed by common DLSR (digital single lens
reflex) cameras. The angle of view could exceed 80 degrees along the flight direction when the focal length is 24mm,
and the ratio of base line to height could exceed 0.7 when longitudinal overlap is 60%. Some original and mosaic images
captured by this prototype system in some ground and airborne experiments are given at last. Experimental results of
image test show that the upright imaging method can effectively avoid the oblique deformation and meet the geometrical
precision of image mosaic.
A combined spectral curve is measured by the traditional field spectrometers in a narrow or wide field range, and the traditional spectral curves are mixed inherently because of the low spatial resolving power. So the mixed spectral pixels were used in the traditional works on the mixed pixel decomposition. A new measure method is proposed to replace the point measurement. The spectral data is captured by the dispersal unit, and one spatial data is from the imaging CCD, and another is captured by the scanning mirror. By the new imaging spectrometer, the target image and spectral curves of
every image pixel are captured simultaneously with high spatial resolution. The captured spectral curves could be regarded as the pure curves, which are very useful for the model foundation and analysis of mixed pixel and pixel decomposition. The basic dispersal principle and imaging mode is introduced in this paper. The detailed design is given by the general diagram and the composition figure. The methods and flow chart of the geometric correction and
radiometric calibration are discussed in detail. Some experiments are carried out to measure the vegetation and other typical targets, the results of the images and spectral curves are given and discussed.
The traditional interpolation could achieve a good correcting result when the resolution is almost homogeneous in the whole image. But the resolutions of the images captured by side-looking digital cameras are not uniform, and the resolutions of the image pixels should be taken into consideration. The imaging model of side-looking camera is founded, and the resolution distribution is given by analyzing the imaging equation of side-looking camera. And the resolution along x and y direction is calculated with the parameters of MADC(Multi-model Airborne Digital Camera). For the image processing for the side-looking camera, a new interpolation method is proposed based on the resolution distribution. The new interpolation equations are given for the linear and array CCD images.
Multi-mode Airborne Digital Camera System (MADC) was developed by Institute of Remote Sensing Applications and
Shanghai Institute of Technical Physics in 2006. The system is enhancing and optimizing further now. It could realize
three modes of wide field, multispectral, and stereophotography based on three 4K*4K CCD digital cameras in the
course of taking aerial photography. Several finished aerial experiments have already demonstrated that the system has
good performance for aerial photography; both the software and the hardware of MADC could work stably and reliably.
Multispectral mode is a popular imaging way in airborne remote sensing. It can obtain multi-bands remote sensing
images by using several digital cameras synchronously. The multispectral images can make use for various remote
sensing applications, such as environment monitoring, resource researching, military use, and so on. In some special
conditions, images which get by using less than 10nm bandwidth narrowband filters can be treat as hyperspectral images;
so that we can consider the multispectral imaging way is a new approach for hyperspectral bands selection and data
acquisition. In this paper, we will mainly discuss the following questions for the multispectral mode of MADC: the
design principle, the basic arithmetic or model, the installation mode, the corresponding aerial experiments, the
application fields and the ways of multitspectral images processing. At the same time, some important accessorial
devices of MADC are also introduced. The point and conclusion will be received based on the practice installation,
operation, ground and aerial experiments.
Optical registration requires the same spatial coordinate of all the corresponding pixels in the multi-spectrum images. The imaging equation of the multi-lens camera is established in the same ground coordinate. Some factors are analyzed and simulated with the actual parameters of a multi-spectral camera. The ground coordinate differences are compared among these factors, and the results are shown in paper. The shutter delay between the camera shutter and POS should be considered firstly, and the influence by focal length is more marked than the influence by angle of optical axis. The multi-spectral cameras should be selected to keep higher shutter synchronism.
For the large need of the high resolving power spatial data, a multi-mode airborne digital camera system (MADC) is researched and integrated which has the characters of wide field, multi-spectrum and stereo imaging. This paper introduces the constitution and the technical specifications. MADC can be combined with Position and Orientation System (POS) to get the orientation data of every image, thus, the geometric correction of the image can be done in case of that there are little or no ground control points (GCP), which saves the heavily late works. Many aerial experiments have been executed, and a mass of high quality images were captured. At last, the perspective of MADC's applications in the remote sensing fields is analyzed.
As a new type of aviation remote sensing earth observation system, the UAVRSS (Unmanned Aerial Vehicle Remote Sensing System) has some special characteristics for getting the digital remote sensing images. Through some real flying experiments of the UAVRSS, the data and the images were obtained. These data and the images were analyzed by three methods from three aspects in this paper. The result shows that it is viable that using the UAV with remote sensing system to achieve the remote sensing works.
In projection Aero-Digital Camera with Large Format Array CCD, High Resolution, Large Field of View and Multi-mode, three cameras with 4k×4k CCD sizes are integrated separately in three modes, including large field of view mode, multi-spectral mode and stereophotography mode. Such methodology make one camera system to meet different roles according to the different setting ways before flight missions. Correspondingly the different modes have different geometric characteristics, and the situation looks like more complicate with some additive factors' variations of aircraft, such as pose, speed, height, and so on.The POS/DG system was carried in flight to aid to the upper geometric correction of CCD images. Some flight pose parameters, such as precision location coordinate, flight pose, dynamic variations etc. were directly used in the geometric correction models. One processing example is also provided in this paper.
This new technique for imaging spectrometry is based on computed-tomography (CT). The obvious feature of this method comparing with other imaging spectrometry is its optical system. Two cylindrical lenses compress a two-dimensional object into a one-dimensional image. Subsequently, the spectral image dispersed by a grating is obtained by two-dimensional detector array. A rotation scanning could collect a series of spectral images with different projection angles. The spectral image of the object is reconstructed from these projection images by computed-tomography algorithm. Although this method still needs a rotation scanning to obtain enough information for giving out the data cube of the object, its energy efficiency, and its signal to noise, could be improved significantly. The optical and mathematical theories of this method are discussed. And the suggested optical configuration has also given. A discrete model of this imaging spectrometric system is established to show the digital reconstruction algorithms. A computer simulation based on the discrete model is executed by MATLAB. The reconstructed results with a defined spectral image indicate that the method is capable of reconstructing scenes containing both broadband samples and narrow-band samples. When the specific noise is added, the impact of the number of projection angles on reconstruction precision is analyzed.