SAR image despeckling method based on improved Frost filtering

Image Speckle Denoising for Securing Internet of Smart Sensors

“…A (i, j) ∈φ n ; φ n represents the unmarked area; (9) end; end; end (10) en the marked area φ u and unmarked area φ n in the noisy image are obtained; (11) Read the image A size [m. n]; (12) for i � 1:m (13) for j � 1:n (14) if current position (i, j) belongs to the marker area φ u (15) 16) else ( 17)…”

“…First, we use the spatially weighted Euclidean distance as the similarity function in the marked area, as shown in formula (4), and appropriate filtering parameters are selected for filtering. Meanwhile, the mean difference of similar blocks is used as the similarity function for weighting in the unmarked region, as shown in equations ( 10) and (11), and appropriate filtering parameters are selected. According to the characteristics of MSTAR image, the new attenuation factor is defined as…”

“…e images of armored vehicles (SAR1) and tanks (SAR2) in the MSTAR dataset are used for verification. We use Frost algorithm [11], SSIM-NLM method [22], MR-NLM method [24], and block-matching 3D (BM3D) algorithm [15] to compare with the proposed algorithm to verify its superiority.…”

“…ere are two main purposes for image denoising in the MSTAR dataset: one is to smooth out the noise-polluted background area and the other is to retain more texture and detail information in the target area [9]. Commonly used SAR image denoising algorithms are divided into spatial domain filtering [10,11], transform domain filtering [12][13][14][15], and partial differential anisotropic diffusion filtering [16,17]. Spatial filtering is mainly based on LEE filtering [10] and Frost filtering [11]; in this method, the corresponding pixel values are processed by sliding a fixed-size window and predefined filter coefficients.…”

“…Commonly used SAR image denoising algorithms are divided into spatial domain filtering [10,11], transform domain filtering [12][13][14][15], and partial differential anisotropic diffusion filtering [16,17]. Spatial filtering is mainly based on LEE filtering [10] and Frost filtering [11]; in this method, the corresponding pixel values are processed by sliding a fixed-size window and predefined filter coefficients. However, the filtering effect is limited by the window size and has the disadvantage of insufficient filtering.…”