Noise
- 1. WHAT IS NOISE ? • Signal noise, in its most basic sense, is any unwanted interference that degrades a communication signal. • in photography, the term digital noise refers to visual distortion. • Noise looks like tiny colored pixels or specks in your photograph, • Noise can distort the visual detail of your photo, making it something that photographers try to avoid. • Several factors can affect the level of noise, including sensor size, higher ISO settings, and long exposures
- 2. Noise is very difficult to remove it from the digital images without the prior knowledge of noise model. Noise sources Image acquisition Image transmission
- 3. NOISE
- 4. NOISE MODELS • Noise produces undesirable effects such as artifacts, unrealistic edges, unseen lines, corners, blurred objects and disturbs background scenes. • To reduce these undesirable effects, prior learning of noise models is essential for further processing. • Digital noise may arise from various kinds of sources such as Charge Coupled Device (CCD) and Complementary Metal Oxide Semiconductor (CMOS) sensors. • Points spreading function (PSF) , Modulation transfer function (MTF) , Probability density function (PDF) or Histogram is used to design and characterize the noise models.
- 5. Gaussian Noise Model • It is also called as electronic noise because it arises in amplifiers or detectors. Gaussian noise caused by natural sources such as thermal vibration of atoms and discrete nature of radiation of warm objects. Gaussian noise generally disturbs the gray values in digital images. That is why Gaussian noise model essentially designed and characteristics by its PDF or normalizes histogram with respect to gray value.
- 7. Impulse Valued Noise (Salt and Pepper Noise) 1. This is also called data drop noise because statistically its drop the original data values. This noise is also referred as salt and pepper noise. However the image is not fully corrupted by salt and pepper noise instead of some pixel values are changed in the image. 2. This noise is seen in data transmission. Image pixel values are replaced by corrupted pixel values either maximum ‘or’ minimum pixel value i.e., 255 ‘or’ 0 respectively. 3. Salt and Pepper noise generally corrupted the digital image by malfunctioning of pixel elements in camera sensors, faluty memory space in storage, errors in digitization pro.cess and many more
- 13. DIFFERENT TYPES OF FILTERS USED TO REMOVE THESE NOISES: Mean Filter Mean filter is an averaging linear filter. Here the filter computes the average value of the corrupted image in a pre decided area. Then the center pixel intensity value is replaced by that average value. The mean filter is a simple spatial filter. It is sliding- window filters that replace the center value in the window. It replaces with the average mean of all the pixel values in the kernel or window. The window is usually square but it can be of any shape.
- 14. Arithmetic Mean Filter Find the arithmetic average of the pixel values in the window. Smooth out local variations in an image. Tend to blur the image. Works best with gaussian and uniform noise. Geometric Mean Filter Works best with gaussian noise. Retains detail better than arithmetic mean filter. Ineffective in the presence of pepper noise (if very low values present in the window, the equation will return a very small number). Harmonic Mean Filter Works with gaussian noise. Retains detail better than arithmetic mean filter. Works well with pepper noise.
- 15. Median filter Median filter is a best order static, non- linear filter, whose response is based on the ranking of pixel values contained in the filter region. Here the center value of the pixel is replaced by the median of the pixel values under the filter region. It is easy to implement method of smoothing images. Median filter is used for reducing the amount of intensity variation between one pixel and the other pixel. Trimmed Median Filters Trimmed median filter is used to reject the noise from the selected window. Alpha trimmed mean filter (ATMF) is a symmetric filter where the trimming is symmetric at both ends.
- 16. Standard Median Filters Used to remove impulse noise due to its simplicity and effective noise suppression capability. Median filters are implemented uniformly across the image and thus tend to modify both noisy and non noisy pixels. Effective removal of impulse using median filter is often accomplished at the expense of blurred and distorted features.. It is effective only for low noise densities. Adaptive Median Filter AMF is a non linear filter. It uses varying window size for noise reduction. AMF fairs well at low and medium noise densities but blurs the image at high noise densities.( Window size is increased which in turn blurs the image). Switched Median Filters Modification of simple median filter. These filters work on the basis of impulse detection and correction. Noise detection process determines corrupted pixels and uncorrupted pixel prior to applying filtering