Speckle is the dominant noise in SAR imagery. It is due to multiple coherent reflections from the ambience around the target. Multi looking or adaptive edge preserving filtering can be used to remove the noise.
Speckle is signal correlated noise. In ultrasound imagery also other sources of noise are presente depending on the specific application. At least one has to consider the thermal and electronic noise added at the receiver.
Agree with Cataldo, in Ultrasound imaging, speckle is the major noise source and very low SNR.
Even Radar and SAR images will have Speckle noise, compare to US images SAR has got more speckle noise.
Speckle noise is of multiplicative nature. It reflects the image aquisition mechansm. The Gaussian noise reflects the quality of the input sensor.
@Dinesh, are you considering an array of ultrasound TX/RX in filtering? (most advanced filtering methods do). Given the next two answers, it is a must and obviously advanced signal processing methods are required, possibly running on non-standard computer architectures.
Speckle is the dominant noise in SAR imagery. It is due to multiple coherent reflections from the ambience around the target. Multi looking or adaptive edge preserving filtering can be used to remove the noise.
To my knowledge, ultrasound (US) speckle cannot be considered as noise, but as an interference pattern. I believe 'image noise' is usually random, but US speckle is not random and the same interference pattern can be regenerated. Actually, sometimes speckle do help to identify the boundaries better in US images, than without speckle. However, I know that it is very common to refer to it as noise in the literature.
In addition to speckle, there is thermal noise in US images, arising due to electronics.
Speckle "noise" arises from constructive or destructive interference in coherent imaging systems. It is multiplicative in nature - ie. it is directly proportional to the local grey level in the area.
The signal and noise are not directly correlated to each other. Speckle is statistically independent to the information in the area.
The Rayleigh speckle model often best fits the distribution of speckle in 1-looked SAR images in homogeneous areas of coarse resolution images. The K distribution better describes speckle statistics for heterogeneous areas in fine resolution images.
A good source of information - Polarimetric Radar Imaging - Lee, Pottier pp 101
The noise is multiplicative i.e. speckle, see also :
C.P. Loizou, C.S. Pattichis, “Despeckle filtering algorithms and software for ultrasound imaging,” Synthesis Lectures on Algorithms and Software for Engineering, Ed. Morgan & Claypool Publishers, 1537 Fourth Street, Suite 228, San Rafael, CA 94901 USA, June 2008, ISBN-13: 9781598296204
help me ti know about the all type of noise in medical ultrasound image and its filtering process
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