Survey of image denoising techniques <s> Introduction <s> The paper introduces a novel speckle reduction method based on thresholding the wavelet coefficients of the logarithmically transformed image. The method is computational efficient and can significantly reduce the speckle while preserving the resolution of the original image. Both soft and hard thresholding schemes are studied and the results are compared. When fully polarimetric SAR images are available, the authors propose several approaches to combine the data from different polarizations to achieve even better performance. Wavelet processed imagery is shown to provide better detection performance for the synthetic-aperture radar (SAR) based automatic target detection/recognition (ATD/R) problem. > <s> BIB001 </s> Survey of image denoising techniques <s> Introduction <s> Sunroof apparatus is provided for a passenger motor vehicle, which apparatus includes a rigid movable cover member for closing a sunroof opening. In order to minimize the space taken by the drive mechanism for moving the cover member to open positions from the closed position thereof, a single incompressible drive cable is provided which has one end attached to a guide element at one lateral side of the cover member and the other opposite end attached to a guide element at the opposite lateral side of the cover member. A cable driving mechanism such as an electric motor is disposed intermediate the ends of the cable for drivingly moving the same in respective opposite directions. The cable is guided and attached to the guide elements so that, upon movement of the cable in one direction, the guide element at one side of the vehicle is pulled in a first axial direction of the vehicle and the guide element at the opposite lateral side of the vehicle is pulled in the same axial direction. In preferred embodiments, the guide elements are constructed so as to accommodate sliding, tilting, and combined sliding and tilting movement of the cover member with respect to the adjacent roof panel structure in response to movement of the guide elements. <s> BIB002
Digital images play an important role both in daily life applications such as satellite television, magnetic resonance imaging, computer tomography as well as in areas of research and technology such as geographical information systems and astronomy. Data sets collected by image sensors are generally contaminated by noise. Imperfect instruments, problems with the data acquisition process, and interfering natural phenomena can all degrade the data of interest. Furthermore, noise can be introduced by transmission errors and compression. Thus, denoising is often a necessary and the first step to be taken before the images data is analyzed. It is necessary to apply an efficient denoising technique to compensate for such data corruption. Image denoising still remains a challenge for researchers because noise removal introduces artifacts and causes blurring of the images. This paper describes different methodologies for noise reduction (or denoising) giving an insight as to which algorithm should be used to find the most reliable estimate of the original image data given its degraded version. Noise modeling in images is greatly affected by capturing instruments, data transmission media, image quantization and discrete sources of radiation. Different algorithms are used depending on the noise model. Most of the natural images are assumed to have additive random noise which is modeled as a Gaussian. Speckle noise BIB001 is observed in ultrasound images whereas Rician noise BIB002 affects MRI images. The scope of the paper is to focus on noise removal techniques for natural images.