Search results for "Top-hat transform"
showing 5 items of 5 documents
Rank-order and morphological enhancement of image details with an optoelectronic processor.
2010
In all-optical processors, enhancement of image details is the result of high-pass filtering. We describe an optoelectronic processor in which detail enhancement results from the digitally calculated difference between an original input image and its low-pass filtered version. The low-pass filtering is realized through the rank-order median and the morphological opening and closing operations calculated by use of the optical convolver. It is shown that the normalized difference between the morphological white and black top hats enhances bright and dark image details analogously to the rank-order unsharp masking.
Digital Image Processing in the Analysis of Astrometric Plates
1991
AbstractIn this paper, we display an improvement to our process of semi-automatic measuring of astrometric plates, in which the photometric sensor is substituted by a CCD system of image getting and digitalization. The advantages of this method are analyzed taking into account the possibilities of the image analysis in the space and frequency domain.
A note on the iterative object symmetry transform
2004
This paper introduces a new operator named the iterated object transform that is computed by combining the object symmetry transform with the morphological operator erosion. This new operator has been applied on both binary and gray levels images showing the ability to grasp the internal structure of a digital object. We present also some experiments on artificial and real images and potential applications.
Fractional wavelet transform
1997
The wavelet transform, which has had a growing importance in signal and image processing, has been generalized by association with both the wavelet transform and the fractional Fourier transform. Possible implementations of the new transformation are in image compression, image transmission, transient signal processing, etc. Computer simulations demonstrate the abilities of the novel transform. Optical implementation of this transform is briefly discussed.
Merging the transform step and the quantization step for Karhunen-Loeve transform based image compression
2000
Transform coding is one of the most important methods for lossy image compression. The optimum linear transform - known as Karhunen-Loeve transform (KLT) - was difficult to implement in the classic way. Now, due to continuous improvements in neural network's performance, the KLT method becomes more topical then ever. We propose a new scheme where the quantization step is merged together with the transform step during the learning phase. The new method is tested for different levels of quantization and for different types of quantizers. Experimental results presented in the paper prove that the new proposed scheme always gives better results than the state-of-the-art solution.