An adaptive area contrast enhancement algorithm is proposed to solve the problem of low contrast in agricultural images. The algorithm automatically detects low contrast regions using local standard deviation and Sobel gradient and selectively applies CLAHE and unsharp masking techniques to them. The method, tested on the SIRI-WHU database, provided an improvement of 21.9% in terms of BRISQUE metric and 37.7% in terms of GCF. On average, 40% of the images were identified as low contrast, and only these regions were processed. Compared with the Global CLAHE, Histogram Equalization, Gamma Correction, and Unsharp Masking methods.
| Mualliflar | Jalelova, Malika, Seytnazarova, Aygul |
|---|---|
| Jurnal | Al-Farg'oniy avlodlari |
| Nashr sanasi | 2026-06-07 |
| Son | 2 |
| Betlar | 341-345 |
| Til | Rus |
kontrast oshirish, qishloq xo‘jaligi tasvirlari, uchuvchisiz uchar qurilmalar, Sobel, standart og‘ish, algoritm, CLAHE, BRISQUE, Global Contrast Factor, contrast enhancement,agricultural imagery,drones,Sobel,standard deviation,algorithm,CLAHE,BRISQUE,Global Contrast Factor
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