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Image compression is minimizing the size in bytes of a graphics file without degrading the quality of the image to an unacceptable level ,the reduction in file size allows more images to be stored in a given amount of disk or memory space, it also reduces the time required for images to be sent over the ground This paper presents a new coding scheme for satellite images. In this study we apply the fast Fourier transform and the scalar quantization for standard LENA image and satellite image, The results obtained after the (SQ) phase are encoded using entropy encoding, after decompression, the results show that it is possible to achieve higher compression ratios, more than 78%, the results are discussed in the paper.

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Abstract:The first of the new generation of Meteosat satellites, known as Meteosat Second Generation (MSG-1), was launched in August 2002. As with the current Meteosat series, MSG is spinstabilized and capable of greatly enhanced Earth observations. The satellite's 12-channel imager, known formally as the Spinning Enhanced Visible and Infrared Imager (SEVIRI), observes the full disk of the Earth with an unprecedented repeat cycle of 15 min in 12 spectral wavelength regions or channels. Our goal is to collect maximum MSG images data with our real time acquisition system, to trust the continuous observation of the Earth's full disk with a multi-spectral imager. This research gives an overview of the MSG SEVIRI instrument, the general approach for the active fire monitoring and the description of the algorithm together with the practical application of the tests and the algorithm. The AFMA algorithm (Active Fire Monitoring Algorithm) developed in this work is able to detect most of the existing active fires with a minimum of false alarms. The AFMA algorithm distinguishes between Diurnal and Nocturnal periods of day. The algorithm itself is based on a simple threshold algorithm. A few results are described and discussed.

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Satellite image Compression reduces redundancy in data representation in order to achieve saving in the cost of storage and transmission image compression compensates for the limited on-board resources, in terms of mass memory and downlink bandwidth and thus it provides a solution to the (bandwidth vs. data volume) dilemma of modern spacecraft Thus compression is very important feature in payload image processing units of many satellites, In this paper, an improvement of the quantization step of the input vectors has been proposed. The k-nearest neighbour (KNN) algorithm was used on each axis. The three classifications considered as three independent sources of information, are combined in the framework of the evidence theory the best code vector is then selected. After Huffman schemes is applied for encoding and decoding.

The first of the new generation of Meteosat satellites, known as Meteosat Second Generation (MSG-1), was launched in August 2002. As with the current Meteosat series, MSG is spinstabilized and capable of greatly enhanced Earth observations. The satellite's 12-channel imager, known formally as the Spinning Enhanced Visible and Infrared Imager (SEVIRI), observes the full disk of the Earth with an unprecedented repeat cycle of 15 min in 12 spectral wavelength regions or channels. Our goal is to collect maximum MSG images data with our real time acquisition system, to trust the continuous observation of the Earth's full disk with a multi-spectral imager. This research gives an overview of the MSG SEVIRI instrument, the general approach for the active fire monitoring and the description of the algorithm together with the practical application of the tests and the algorithm. The AFMA algorithm (Active Fire Monitoring Algorithm) developed in this work is able to detect most of the existing active fires with a minimum of false alarms. The AFMA algorithm distinguishes between Diurnal and Nocturnal periods of day. The algorithm itself is based on a simple threshold algorithm. A few results are described and discussed.

No abstract