Design of Hybrid Filter With Wavelet Denoising

Design of Hybrid Filter With Wavelet Denoising Simranjit Kaur DESIGN OF HYBRID FILTER WITH WAVELET DENOISING AND ANISOTROPIC DIFFUSION FILTER FOR IMAGE DESPECKLING 1. INTRODUCTION Digital images are images which are formed of picture elements also termed as pixels. The pixels typically are arranged in a rectangular array. The dimensions of the pixel array determine its size. Its width is defined by the number of columns, and height by the number of rows in that array. Digital images are susceptible to various types of noise.Speckleis a form of noise which exists in and decreases the quality of the active  radar  and  synthetic aperture radar  (SAR) images. Image denoising is an essential task in image processing, both as a component in other processes and as a process itself. Various methods are there to denoise the image. A good image denoising model preserves edges, while removing noise. If the window size is quite large, then the over smoothing will occur and edges become blur out. If the size of window is small, then the smoothing property of the window decreases and doesn’t remove the speckle noise that efficiently. Secondly, in the traditional filters there is no enhancement of edges. Thirdly these existing filters are non directional. Finally, the thresholds which are used in the existing filters, although are inspired by statistical arguments, they are ad hoc improvements which only display the drawbacks of the window-based approach. So, inorder to alleviate this problem, hybrid filter with Wavelet denoising and anisotropic diffusion filter, has been proposed. In this model, we work on the drawbacks of the previous models such as oversmoothing of the images and unnecessaryremoval of the edges. 1.1 SCOPE OF STUDY The scope of work for this model is finding an accurate technique for the development of a hybrid despeckling model whose main purpose is to preserve the edges of the image and avoid oversmoothing during denoising. We have to study various previous techniques and on the basis of the study we will develop a model which overcomes the flaws of existing despeckling methods while improving the quality parameters in the end of filtering process. 2. OBJECTIVES To reduce the speckle noise. To improve the parameters like peak signal to noise ratio, equivalent no of looks and coefficient of correlation. Tocreate a better image processing algorithm To investigate the proper selection of wavelet filters and thresholding scheme which yields optimal visual enhancement of SAR images. Tocreate a better image processing algorithm for denoising technique. To design a hybrid filter from the two existing filters for removal of noise in uniform regions from the image. 3. BRIEF LITERATURE SURVEY Until now, several researches and case studies have been reported about wavelet denoising . Yuan Gao and Zhengyao Bai [2] proposed a speckle reduction method which is based on curvelet domain in SAR images. In this technique, curvelet transform is mapped with wavelet filtering. In the first step, multiplicative noise is converted in to additive noise. Second step is to compute the threshold, by using soft and hard thresholding curvelet coefficients are thresholded. Lastly, opposite CT and exponential transform are applied to reconstruct the original image. This shows that this method is better than other filtering techniques. S.Sudha et al. [3] proposed a tool for noise removal in ultrasound images. The comparison shows that the proposed technique provides better results than other existing techniques. Manish Goyal and Gianetan Singh Sekhon [4] applied wavelet based hybrid thresholding techniques: firstly applied the statistical technique and then filtering based on bayes threshold. Then results are calculated which is followed by applying soft thresholding. The experimental results show that this filter gives better results. Alka Vishwa, Shilpa Sharma [5] created a simple context-based model for the selection of threshold within a wavelet denoising model. Estimations of the local variance with appropriate weights are used for thresholding. Although, it is seen that the denoised image, during removal of a substantial amount of noise also suffers practically node gradation in the sharpness and details. The experimental result shows that this proposed method yields significantly improved visual quality and also better PSNR in comparison with the other techniques for the denoising. Rohit Verma,Jahid Ali [6] has discussed different types of noise that can creep in image during acquisition. In the second section various filtering techniques are presented that can be used for denoising the digital image. Experimental results found that the BM3D along with median filters gave better results and the averaging and minimum filters performed the worst. BM3D is best choice of removing Salt and pepper noise. In all other cases median filter is considered more suitable. K.Bala Prakash ,R.Venu Babu and Venu Gopal [7] proposed a new technique which is independently select the filter for different types of images. In this technique a new independent filter will automatically check which filter gives better results in images,. The results are computed using different parameters. The experimental results shows that proposed technique gives better results than other techniques. Mashaly et al. [8] introduced a new technique which is based on morphological operations. In this paper Synthetic aperture radar images are used. In this morphological operations are applied to remove the speckle noise reduction and the results are compared with different filtering techniques such as adaptive and non adaptive filters. Adib Akl and Charles Yaacoub [9] proposed a method for image denoising that uses wavelet denoising and an adaptive form of the Kuan filter that results in a significant removal of speckle noise. The results are tested in respect of the peak signal to noise ratio, equivalent no of looks and coefficient of correlation. Udomhunskal and Wongsita [10] presented a method for Ultrasonicspeckledenoisingusingthe hybrid technique which is based on wavelet transform and wiener filter to reduce thespecklenoisewhile preserving the details. In this method, firstly apply the 2D discrete wavelet transform for the noisy image. Then, the wiener filter isapplied to each detail subband. The results found that this method removes the ultrasonicspeckle more efficiently. 4. GAPS IN STUDY 5. PROBLEM FORMULATION The basic idea of this model is the estimation of the uncorrupted image from the noisy image or distorted image known as â€Å"image denoising†. To remove noisy distortions, there are various methods to help restore an image. Choosing the best method plays a very important role for getting the desired image. There are various existing techniques to remove the Speckle Noise Reduction but due to some drawbacks these techniques cannot remove Speckle Noise efficiently. The major drawbacks of the existing filters are: The adaptive filters like Lee filter, Kuan filter and Frost filter are not able to perform a full removal of Speckle without losing any edges because they rely on local statistical data and this Statistical data related to the filtered pixel value and this data depends upon the filter window over an area. As these existing filters are very much sensitive to the Window Shape and Window Size. If the Window Shape is very much larger than over smoothing will occurs. As window size is smaller than the Smoothing Capability of the Window will decrease. So, to overcome these limitations we proposed a new hybrid technique that combines Wavelet based denoising and anisotropic diffusion filter. As Wavelet is Frame based Approach, it does not dependent on Space or Time. Wavelet also provides better Resolution. In Anisotropic diffusion filter, it is based on partial differential equation. It does not depends upon the window size but, on Mean Square Error approach. So it provides better filtering capability and enhances the edges. By applying these techniques the efficiency of the system is increased and noise is reduced to the greater extent. 6.METHODOLOGY Wavelet denoising is a modern approach to denoising which is not based on local statistical data. The wavelet denoising is a frame based approach. In this approach, a wavelet transform is applied on the image, followed by thresholding method. In the end, an inverse wavelet transform is applied to the image for lengthening the image components after they were reduced during wavelet decomposition. A speckled image can be expressed in the form of k=m*n Where m is the original image and the n is noise with mean and unknown variance. The following diagram explains the DWT-denoising.Wavelet-based denoising consists of: Applying the Discrete Wavelet Transform (DWT) to the noisy image k, Thresholding the detail coefficients, and Finally applying inverse discrete wavelet transform (IDWT) technique on the threshold coefficients to obtain an estimation of the original image kas shown in Figure1. Figure1. Block diagram of wavelet denoising Theimage k is inserted in the filter in the logarithmic form i.e. k=m+n. After wavelet transform W is applied, it results in W(k). W(k) undergoes the thresholding process which results in T(W(k)) which is represented asfwin the figure 1.Finally, the de-speckled image is extracted using the inverse transform W-1. Anisotropic diffusion filter: In anisotropic diffusion the main method is to smoothen within the region in preference to the smoothening across the edges. Without bias due to the filter window shape and size the partial differential equation based removal approach allows the generation of image scales consisting of set of filtered image. So, anisotropic diffusion is adaptive and does not utilize the hard thresholds to alter performance in homogeneous areas or in region near edges and small features. This is quite edge sensitive. In the anisotropic diffusion filter, conduction coefficient is taken to be one within given region it is zero near the edges. Equation for anisotropic diffusion is as given I (x, 0) = =div (F) + – Here I is input image, is the initial image, div (F) is diffusion flux and is entire coefficient Overview of Framework First load the image using a MATLAB processing tool box and add speckle noise into in the image which can be seen in the form black and white dots. After image is loaded it will pass through wavelet denoising filter where log transformation is applied so as to decrease the multiplicative nature of the image by making it additive for easing the removal process.Here Bayes Shrink Threshold is used for thresholding process. The Bayesian Shrinkage contains a soft-threshold and minimizes the Bayesian risk. Shrink threshold is calculated by considering a Generalized Gaussian Distribution. After that an Inverse wavelet transform will be applied on the threshold output, so as to extract the image. After applying the Wavelet Transform, hybrid of the anisotropic filter and wavelet will be formed, sothat it provides better results than simple Wavelet denoising techniques. After the image passes through the filter, results will be evaluated in terms of peak signal to noise ratio, Coefficient of c orrelation and equivalent No of looks. These results will show that the hybrid model gives better results than other existing techniques. Figure 2.Basic flowchart depicting the despeckling of an image using hybrid model. 7. FACILITIES REQUIRED FOR PROPOSED WORK The various hardware and software facilities of the proposed model are given as under : Hardware Requirements: Intel Core CPU 3 GB RAM Windows server Software Requirements: MATLAB Software(R2012a) 32 bit (win32) 8. PROPOSED PLACE OF WORK Department of Computer Science Engineering, Chandigarh Engineering College, Landran Mohali, India REFERENCES

An Interview With a Relative

Welcome to the blue collar city of Buffalo, New York. I find myself in my great Uncle Wills old brick home in the center of South Buffalo. The house has the familiar smell of old people, in the foyer are a pair of work boots the leather old and worn, the soles nearly depleted. A layer of dust has formed on the boots that have remained untouched for decades. As I move closer to the kitchen I can hear the recognizable sound of stainless steel clinking on ceramic, the rhythmic noise can only be one thing; Uncle Will’s stirring his ever present cup of joe. I know this interview is going to take a bit so I head to the fridge to find a cold beverage. Inside the fridge, prune juice I thought â€Å"ugh†, tap water will do. My Uncle begins by interviewing me. Uncle Will is curious to know how I’m doing in school and if I like living in Kansas. We talk about family, cars and pets(he has a very fat cat). I don’t want this interview to be formal and stiff so I casually guide the conversation to his earlier years. I want to ask him about WWII but this is not what I want to focus on. I do ask about his service in the United States Army just to get an idea of how his time in the army prepared him for entering the job market. In his tour of duty he saw himself promoted three times, eventually to the rank of Captain and led a company of sixty men. This is all I want to know of his brief military service. I ask about his homecoming and the first thing he mentions is the excellent growth the economy in Buffalo has made, â€Å"it was as if the depression never happened† he says with a half smile and a look of satisfaction. The best thing is not only was the city of Buffalo prospering the entire nation from the Atlantic to the Pacific was too. I sit quiet and attentive just letting him talk. It’s like a history lecture only it’s just me front and center, completely interested in the subject. I want to know more about Buffalo and the jobs available to him so I implore. â€Å"You could just see the smiles on everyone’s faces, people walking with a bounce in their step† he tells me. The reason for the smiling faces was that Buffalo was home to Bethlehem Steel the second largest steel producer in the nation. Bethlehem Steel employed tens of thousands of the city’s people they offered good wages and a unionized work force, these things kept the grins ear to ear. The steel was mainly sent to Detroit to fuel the auto industries record sales. The primary means to transport the steel was the railroad and this is where Uncle Will found his calling. He was hired for the job almost immediately. His time leading troops in combat made him the top choice for the conductor position. Old Will describes his new job as â€Å"Love at First sight†. Will adored the sound of the methodic turning of the locomotives wheels, the hustle and bustle of the train yard and the fact that he had the privilege to literally drive the economy in a 200 ton, 7000 horsepower machine. â€Å"The most efficient means of transportation, steel on steel,† he says proudly. He now commanded trains with at least sixty box cars just like the company of soldiers he led just a short while ago. Uncle Will informs me that though the job often kept him away a lot with trips to Chicago and other mid-western cities he was proud to be transporting the materials to help the U. S prosper. He coveted every moment he spent with his locomotive the diesel powered Dual-Service Erie-Built Train Master, â€Å"I called her Audrey after Audrey Hepburn, they showed her movies to us in the service† Uncle Will laughs as he finishes his statement. Audrey was navigating her way through the extensive network of railways across the country and with that even I feel a bit of admiration of the industry. His devotion to the train industry is fascinating. I ask him to tell me more about his duties as a conductor. The conductor has the duty of accelerating, breaking, changing tracks and supervising the crew, pretty important,† he adds with a chuckle. His days on the helm of the locomotive began to blur together days became months and months turned to years but he says â€Å" every time I pushed the accelerator I still had that goose bump sensation I felt the first time I pushed her to full speed. † Buffalo was still enjoying economic growth through the sixti es still thriving on America’s appetite for steel. In the late sixties as my Uncle explained he noticed a change, less noise at the rail yard the sound of wheels turning was less prevalent the methodic rhythm slowing down just like buffalo’s economy. Everyone could sense the change and the smiles began to fade. I want to know the reason for this change in demand. Uncle Will proclaimed with anger in his voice â€Å"Foreign steel was being imported from places like China and Korea. It was much cheaper and industry wants to save money. † The lack of demand for Buffalo’s number one export closed the doors of Bethlehem and Republic Steel. Thousand lost their jobs. â€Å"You could call this moment in time the death of our city â€Å"he adds. This was and is the beginning of the continual decline of the Queen City. Uncle Will was right unemployment rates were 6% and today is 9. 6% according to the New York State Department of Labor (www. labor. state. ny. us). This downturn affected all subsequent history. Unemployment caused crime rates to rise, drug use was rampant on the east side of town and it was spreading at a rapid rate. Today buffalo is littered with abandoned homes even ornate Roman Catholic churches have seen their doors and windows boarded up. â€Å"The city as I knew it was gone† with these words I hear a solemn sigh. I wanted this interview to be about how the railroad industry affected his life however by the way it started I should have known the interview was just a means for Uncle Will to tell me about the city he watched grow to greatness and the sadness it brings him to watch its decline. I peer out the window there is a light blanket of snow covering the concrete and the small bush he has in his front yard. It looks pretty and peaceful but looks can be deceiving. Uncle Will mention’s that even in his neighborhood crime was creeping in â€Å"the house just two doors down was burglarized just a week ago† he proclaims with a deep sadness in his eyes. I look closer at Uncle William’s face tired and worn like the work boots in the front hall, his soul wearing away. This man has done so much in his life he volunteered when his country needed him and guided trains on the veins of Buffalo, pumping its blood of steel around the fledging nation. Without sadness there cannot be joy and without depression there cannot be growth. Unfortunately this weary old man is still sitting in his old red recliner coffee cup in hand staring out the window at the city streets once home to the laughter of playing children now quiet and desolate. He says â€Å"I’d leave this place but there are too many memories in this old house, too many memories in this old city. †

Mary Wollstonecraft and Mary Shelley

Mary Wollstonecraft was a pioneer in feminist thinking and writing. The author gave birth to Mary Wollstonecraft Shelley in 1797. Wollstonecraft died soon after childbirth due to a fever. How could this have influenced Shelley’s writings? Although her mother did not live long enough to influence Shelley directly, it is clear that the Wollstonecraft and the ideas of the Romantic era greatly shaped Shelley’s beliefs. The Life of Mary Wollstonecraft Wollstonecraft was strongly influenced by Thomas Paine and argued that women deserved equal rights. She saw how her own father treated her mother as property and refused to allow the same future for herself. When she became old enough, she earned a living as a governess but was bored with this work. She wanted to challenge her high intellect. When she was 28, she wrote a semi-autobiographical novel titled Maria. She soon moved to London and became an admired professional writer and editor who wrote about the rights of women and children. In 1790, Wollstonecraft wrote her essay A Vindication of the Rights of Men based on her reaction to the French Revolution. This essay influenced her famous feminist social study A Vindication of the Rights of Woman, which she wrote two years later. The work continues to be read in literature and Womens studies classes today. Wollstonecraft experienced two romantic affairs and gave birth to Fanny before falling in love with William Godwin. By November  1796, she became pregnant with their only child, Mary Wollstonecraft Shelley. Godwin and she were married in March of the following year. During the summer, she began writing The Wrongs of Women: or Maria. Shelley was born on August 30 and Wollstonecraft died less than two weeks later. Godwin raised both Fanny and Mary surrounded by philosophers and poets, such as Coleridge and Lamb. He also taught Mary to read and spell her name by having her trace her mothers inscription on the stone. Mary Shelley and Frankenstein With much of the independent spirit that drove her mother, Mary left home when she was 16 to live with her lover, Percy Shelley, who was unhappily married at the time. Society and even her father treated her as an outcast. This rejection influenced her writings greatly. Along with the suicides of Percys estranged wife and then Marys half-sister Fanny, her alienated status inspired her to write her greatest work, Frankenstein. Frankenstein is often referenced as the start of Science Fiction. Legend  claims that Shelley wrote the whole book in one night as part of a competition between herself, Percy Shelley, Lord Byron and John Polidori. The aim was to see who could write the best horror story. While Shelleys tale isnt usually classified as a horror it did spawn a new genre mixing moral questions with science.

Case Study Matrix Management Structure - 964 Words

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