Adaptive spatial filtering method based on neighborhood
A spatial filtering and self-adaptive technology, applied in image data processing, instrumentation, computing, etc., can solve the problems of blurred boundaries, reduce the reliability and accuracy of change detection results, improve the degree of automation, and improve the intra-class quality, noise reduction effect
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[0026] Detailed steps of the present invention are as follows:
[0027] Image data description: JN data is the original image data acquired by QuickBird satellite, and the spectral ranges included are blue band (0.45-0.52m), green band (0.52-0.59m), red band (0.63-0.69m), Near-infrared band (0.77-0.89m), and the original image contains multiple types of ground objects and scenes.
[0028] Step 1. Initialize each pixel of the input image, take each pixel as the center point of the window, and obtain the corresponding window pixel value with a window of size 3×3.
[0029] Step 2, count each pixel value obtained by the 3×3 window, and sort (from small to large), and obtain the upper quartile pixel point Up_quartile_pixel and the lower quartile pixel point Low_quartile_pixel.
[0030] Step 3, for each pixel as the seed pixel Pixel, the upper quartile pixel and the lower quartile pixel are used as constraints to perform adaptive neighborhood point expansion (Low_quartile_pixel≤Pix...
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