Nonlinear adaptive filters for speckle suppression in ultrasonic images
Signal Processing
Aggressive region growing for speckle reduction in ultrasound images
Pattern Recognition Letters - Speciqal issue: Ultrasonic image processing and analysis
Brief paper: A swarm intelligence approach to the synthesis of two-dimensional IIR filters
Engineering Applications of Artificial Intelligence
Finding out general tendencies in speckle noise reduction in ultrasound images
Expert Systems with Applications: An International Journal
Nonlocal means-based speckle filtering for ultrasound images
IEEE Transactions on Image Processing
Passive, Active, and Digital Filters
Passive, Active, and Digital Filters
Performance evaluation of a region growing procedure for mammographic breast lesion identification
Computer Standards & Interfaces
Speckle reduction of ultrasound images based on Rayleigh-trimmed anisotropic diffusion filter
Pattern Recognition Letters
SAR image segmentation based on Artificial Bee Colony algorithm
Applied Soft Computing
A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Enhancement and Noise Filtering by Use of Local Statistics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive Noise Smoothing Filter for Images with Signal-Dependent Noise
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iterative Wiener filters for image restoration
IEEE Transactions on Signal Processing
Adaptive filtering noisy transcranial Doppler signal by using artificial bee colony algorithm
Engineering Applications of Artificial Intelligence
Directionlet-based denoising of SAR images using a Cauchy model
Signal Processing
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In this study a novel approach based on 2D FIR filters is presented for denoising digital images. In this approach the filter coefficients of 2D FIR filters were optimized using the Artificial Bee Colony (ABC) algorithm. To obtain the best filter design, the filter coefficients were tested with different numbers (3x3, 5x5, 7x7, 11x11) and connection types (cascade and parallel) during optimization. First, the speckle noise with variances of 1, 0.6, 0.8 and 0.2 respectively was added to the synthetic test image. Later, these noisy images were denoised with both the proposed approach and other well-known filter types such as Gaussian, mean and average filters. For image quality determination metrics such as mean square error (MSE), peak signal-to-noise ratio (PSNR) and signal-to-noise ratio (SNR) were used. Even in the case of noise having maximum variance (the most noisy), the proposed approach performed better than other filtering methods did on the noisy test images. In addition to test images, speckle noise with a variance of 1 was added to a fetal ultrasound image, and this noisy image was denoised with very high PSNR and SNR values. The performance of the proposed approach was also tested on several clinical ultrasound images such as those obtained from ovarian, abdomen and liver tissues. The results of this study showed that the 2D FIR filters designed based on ABC optimization can eliminate speckle noise quite well on noise added test images and intrinsically noisy ultrasound images.