Applications based on restored satellite images

Satellites orbit the earth and obtain imagery of the ground below. The quality of satellite images is affected by the properties of the atmospheric imaging path, which degrade the image by blurring it and reducing its contrast. Applications involving satellite images are many and varied. Imaging systems are also different technologically and in their physical and optical characteristics such as sensor types, resolution, field of view (FOV), spectral range of the acquiring channels - from the visible to the thermal IR (TIR), platforms (mobilization facilities; aircrafts and/or spacecrafts), altitude above ground surface etc. It is important to obtain good quality satellite images because of the variety of applications based on them. The more qualitative is the recorded image, the more information is yielded from the image. The restoration process is conditioned by gathering much data about the atmospheric medium and its characterization. In return, there is a contribution to the applications based on those restorations i.e., satellite communication, warfare against long distance missiles, geographical aspects, agricultural aspects, economical aspects, intelligence, security, military, etc. Several manners to use restored Landsat 7 enhanced thematic mapper plus (ETM+) satellite images are suggested and presented here. In particular, using the restoration results for few potential geographical applications such as color classification and mapping (roads and streets localization) methods.

[1]  Shih-Fu Chang,et al.  Tools and techniques for color image retrieval , 1996, Electronic Imaging.

[2]  Anil K. Jain,et al.  Image retrieval using color and shape , 1996, Pattern Recognit..

[3]  Dan Arbel,et al.  Landsat TM satellite image restoration using Kalman filters , 2004 .

[4]  Mohan S. Kankanhalli,et al.  Color matching for image retrieval , 1995, Pattern Recognit. Lett..

[5]  Dan Arbel,et al.  Criteria for satellite image restoration success , 2003 .

[6]  Alberto Del Bimbo,et al.  Visual Querying By Color Perceptive Regions , 1998, Pattern Recognit..

[7]  Alex Pentland,et al.  Photobook: Content-based manipulation of image databases , 1996, International Journal of Computer Vision.

[8]  Christos Faloutsos,et al.  Efficient and effective Querying by Image Content , 1994, Journal of Intelligent Information Systems.

[9]  Raimondo Schettini Multicolored object recognition and location , 1994, Pattern Recognit. Lett..