Improving SAR image classification in tropical region through fusion with SPOT data

This paper investigates various SAR digital filtering techniques to remove speckles for image classification using fused SAR and SPOT XS image. The fused image classification is then compared with the classified SPOT XS image. The result has shown that the use of the Enhanced Frost digital filtering technique for SAR image and the fusion with SPOT XS gives a very similar classification with comparison to the SPOT XS image classification.</p

Improving vector quantization of satellite images through theapplication of bi-orthogonal wavelets

In image coding applications, vector quantization (VQ) has widely been accepted as an effective compression method for digital images. However, its effectiveness depends greatly on the matching of the VQ elements with the image data values. Prior to the VQ process, orthogonal transforms such as a DCT or FFT are often used to convert an image in the spatial domain to transform coefficients in the frequency domain. In this paper, instead of orthogonal transform coefficients, bi-orthogonal wavelet filters are used to transform a satellite image to the scale-frequency domain. The wavelet coefficients are vector quantized and their statistical features are analyzed in details such as computational complexity and performance efficiency. Some examples will be shown in the presentation to illustrate the advantage of using bi-orthogonal wavelets that can help to improve the matching of VQ elements to the image data values. Through matching the image values, it can be shown that fewer VQ elements would be required to represent the image while maintaining the image quality, Improving the VQ statistical features will in turn increase the compression ratios of image compression of satellite images</p

Development of Q-switched solid-state lasers

The primary aim of this small project is to build a diode pumped solid state laser, to investigate the Q-switched operation of the DPSS laser, and to develop the technique which provides a stable pulse output from a Q-switched DPSS laser.RG 53/9

A novel hybrid bi-orthogonal wavelets/ADPCM algorithm for very lowbit rate satellite image compression

The authors present an overview of remote sensing image compression using wavelet transforms. They begin by describing the wavelet properties that are most important for image compression. In particular, they present a method to construct bi-orthogonal wavelets and their finite impulse response (FIR) filter banks. All of these FIR filter banks all have linear phase characteristics and the signal can be reconstructed exactly. Next, they expound on a novel hybrid scheme that uses bi-orthogonal wavelets and the adaptive differential pulse code modulation (ADPCM) algorithm for very low bit-rate satellite image compression. Complicated SPOT images of city scenes that contain many high frequency details, such as building structures and roads, are used in this investigation. Using their hybrid wavelet/ADPCM compression algorithm, the data integrity of the satellite image was maintained with a peak signal-to-noise ratio (PSNR) of approximately 26 dB while achieving a compression ratio of 150:1.</p

Improving vector quantization of satellite images through theapplication of bi-orthogonal wavelets

In image coding applications, vector quantization (VQ) has widely been accepted as an effective compression method for digital images. However, its effectiveness depends greatly on the matching of the VQ elements with the image data values. Prior to the VQ process, orthogonal transforms such as a DCT or FFT are often used to convert an image in the spatial domain to transform coefficients in the frequency domain. In this paper, instead of orthogonal transform coefficients, bi-orthogonal wavelet filters are used to transform a satellite image to the scale-frequency domain. The wavelet coefficients are vector quantized and their statistical features are analyzed in details such as computational complexity and performance efficiency. Some examples will be shown in the presentation to illustrate the advantage of using bi-orthogonal wavelets that can help to improve the matching of VQ elements to the image data values. Through matching the image values, it can be shown that fewer VQ elements would be required to represent the image while maintaining the image quality, Improving the VQ statistical features will in turn increase the compression ratios of image compression of satellite images</p