An Efficient Image Denoising Approach for the Recovery of Impulse Noise
01 Sep 2017-Bulletin of Electrical Engineering and Informatics (Universitas Ahmad Dahlan)-Vol. 6, Iss: 3, pp 281-286
TL;DR: A hybrid statistical noise suppression technique has been developed for improving the quality of the impulse noisy color images and the performance of the proposed image enhancement scheme is proved using the advanced performance metrics.
Abstract: Image noise is one of the key issues in image processing applications today. The noise will affect the quality of the image and thus degrades the actual information of the image. Visual quality is the prerequisite for many imagery applications such as remote sensing. In recent years, the significance of noise assessment and the recovery of noisy images are increasing. The impulse noise is characterized by replacing a portion of an image’s pixel values with random values Such noise can be introduced due to transmission errors. Accordingly, this paper focuses on the effect of visual quality of the image due to impulse noise during the transmission of images. In this paper, a hybrid statistical noise suppression technique has been developed for improving the quality of the impulse noisy color images. We further proved the performance of the proposed image enhancement scheme using the advanced performance metrics.
Citations
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TL;DR: The proposed deblurring method based on the Wiener filter improved the quality of iris pattern in the blurry image and recorded the fastest execution time to improve thequality of iri pattern compared to the other methods.
Abstract: Iris recognition used the iris features to verify and identify the identity of human. The iris has many advantages such as stability over time, easy to use and high recognition accuracy. However, the poor quality of iris images can degrade the recognition accuracy of iris recognition system. The recognition accuracy of this system is depended on the iris pattern quality captured during the iris acquisition. The iris pattern quality can degrade due to the blurry image. Blurry image happened due to the movement during image acquisition and poor camera resolution. Due to that, a deblurring method based on the Wiener filter was proposed to improve the quality of iris pattern. This work is significant since the proposed method can enhance the quality of iris pattern in the blurry image. Based to the results, the proposed method improved the quality of iris pattern in the blurry image. Moreover, it recorded the fastest execution time to improve the quality of iris pattern compared to the other methods.
9 citations
Cites methods from "An Efficient Image Denoising Approa..."
...Image quality assessment [17], hybrid statistical noise suppression [18] and optimum mean [19] can also be used to enhance the quality of image....
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TL;DR: In many tested images, the proposed method indicates that the noisy pixels are detected efficiently and if the proposed filter is added as a preliminary stage to many filters, the final results will be improved.
Abstract: This paper proposes a new approach for restoring images distorted by fixed-valued impulse noise. The detection process is based on finding the probability of existence of the image pixel. Extensive investigations indicate that the probability of existence of a pixel in an original image is bounded and has a maximum limit. The tested pixel is judged as original if it has probability of existence less than the threshold boundary. In many tested images, the proposed method indicates that the noisy pixels are detected efficiently. Moreover, this method is very fast, easy to implement and has an outstanding performance when compared with other well-known methods. Therefore, if the proposed filter is added as a preliminary stage to many filters, the final results will be improved.
5 citations
Cites methods from "An Efficient Image Denoising Approa..."
...The authors in [15]-[17] proposed a new method based on the value of the noisy pixel and the pixels in the tested window....
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TL;DR: This article proposes the novel noise classification technique found on QTSD (quadruple threshold statistical detection) filter, which is ultimately improved from the outstanding T TSD (Triple Threshold Statistical Detection) filter.
Abstract: Because of the enormous necessity of contemporary noise suppressing algorithms, this article proposes the novel noise classification technique found on QTSD filter improved from the TTSD filter. The four thresholds for each auxiliary situations are incorporated into the proposed QTSD framework for dealing with the limitation of the earlier noise classification technique. The mathematical pattern is modeled by each photograph elements and is investigated in contradiction to the 1 st threshold for analyzing whether it is non-noise or noise photograph elements. Subsequently, the calculated photograph element is analyzed with the contradiction between the 2 nd threshold, which is modeled by using the normal distribution (mean and variance), and is analyzed with the contradiction between the 3 rd threshold, which is modeled by using the quartile distribution (median). Finally, the calculated photograph element is investigated in contradiction to the 4th threshold, which is modeled from maximum or minimum value for analyzing whether it is non-noise or noise photograph elements FIIN. For performance evaluation, extensive noisy photographs are made up of nine photographs under FIIN environment distribution, which are synthesized for investigating the proposed noise classification techniques found on QTSD filter in the objective indicators (noise classification, non-noise classification and overall classification correctness). From these results, the proposed noise classification technique can outstandingly produce the higher correctness than the earlier noise classification techniques.
3 citations
Cites background or methods from "An Efficient Image Denoising Approa..."
...A hybrid statistical noise suppression technique [22] has been proposed for suppressing impulse noise in 2017....
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...Many modern noise suppressing algorithms [22]-[25], which are traditionally comprised of the noise classification technique and the noise recovery technique, have been proposed as following....
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...As a result, the noise classification technique is highly dominant to the overall effectiveness of noise suppressing algorithms thereby extensive advance noise suppressing algorithms [10]-[22] are investigated and developed for both noise classification techniques and noise recovery techniques as following....
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TL;DR: The proposed approach for automatic landmark identification in 3D cephalometric was capable of detecting 12 landmarks on 3D CBCT images which can be facilitate the use of 3Dcephalometry to orthodontists.
Abstract: This study proposes a new contribution to solve the problem of automatic landmarks detection in three-dimensional cephalometry. 3D images obtained from CBCT (cone beam computed tomography) equipment were used for automatic identification of twelve landmarks. The proposed method is based on a local geometry and intensity criteria of skull structures. After the step of preprocessing and binarization, the algorithm segments the skull into three structures using the geometry information of nasal cavity and intensity information of the teeth. Each targeted landmark was detected using local geometrical information of the volume of interest containing this landmark. The ICC and confidence interval (95% CI) for each direction were 0, 91 (0.75 to 0.96) for x- direction; 0.92 (0.83 to 0.97) for y-direction; 0.92 (0.79 to 0.97) for z-direction. The mean error of detection was calculated using the Euclidian distance between the 3D coordinates of manually and automatically detected landmarks. The overall mean error of the algorithm was 2.76 mm with a standard deviation of 1.43 mm. Our proposed approach for automatic landmark identification in 3D cephalometric was capable of detecting 12 landmarks on 3D CBCT images which can be facilitate the use of 3D cephalometry to orthodontists.
1 citations
Cites methods from "An Efficient Image Denoising Approa..."
...Image denoising is very important setp to improve the quality of image [29], many studies doesn’t explain the technique used for noise reduction....
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TL;DR: The implementation of a novel Gaussian smoothing filter with low power approximate adders in Field Programmable Gate Array (FPGA) is discussed, applied to restore the noisy images in the proposed system.
Abstract: Smoothing filters are essential for noise removal and image restoration. Gaussian filters are used in many digital image and video processing systems. Hence the hardware implementation of the Gaussian filter becomes a reliable solution for real time image processing applications. This paper discusses the implementation of a novel Gaussian smoothing filter with low power approximate adders in Field Programmable Gate Array (FPGA). The proposed Gaussian filter is applied to restore the noisy images in the proposed system. Original test images with 512x512 pixels were taken and divided in to 4x4 blocks with 256x256 pixels. The proposed technique has been applied and the performance metrics were measured for various simulation criteria. The proposed algorithm is also implemented using approximate adders, since approximate adders had been recognized as a reliable alternate for error tolerant applications in circuit based metrics such as power, area and delay where the accuracy may be considered for trade off.
1 citations
References
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01 May 2016
TL;DR: A optimized contrast enhancement algorithm that can effectively reduce the color distortion in sky region by solving the atmosphere attenuation model is introduced.
Abstract: The fog images of Inland River often have low contrast. This paper introduces a optimized contrast enhancement algorithm. Firstly, divide the fog image by using the hierarchical searching method of quad-tree subdivision. Choose the brightest pixel as the atmospheric light in the final selected block. Then, combine the Mean Squared Error and the loss function. Next, get the optimal transmission value which can balance the contrast and the information loss. Then, fix the transmission with guide filter and adaptive window slide. Finally, restore the defogged image by solving the atmosphere attenuation model. Compared with the results obtained by several existing classical defogging methods, the experimental result shows that the proposed algorithm can effectively reduce the color distortion in sky region.
7 citations
"An Efficient Image Denoising Approa..." refers methods in this paper
...In [10], an optimal contrast enhancement algorithm is developed and is used to improve the contrast of the fog images....
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TL;DR: It is shown that NASM filter can remove salt and pepper noise effectively meanwhile protect image details well thus getting better filtering performance compared with Traditional Median (TM) filter and other improved Switching Median (SM) filters for laser image.
Abstract: Laser image often mixes with salt and pepper noise when obtained and transmitted by image sensor. The salt and pepper noise not only makes the quality of laser image deteriorated but also causes the detail feature of laser image flooded which contains very important structure information. To remove salt and pepper noise effectively meanwhile ensure image details clear and completed, a Novel Adaptive Switching Median (NASM) filter based on local salt and pepper noise density is presented in this paper. Pixel points are divided into salt and pepper noise points and signal points according to two level detection mechanisms firstly, then, local salt and pepper noise density is introduced here to determined filter window of every noise point, only noise points are filtered by different size window adaptively whereas signal points are kept unprocessed finally. Through analyzing of experimental results, it shows that NASM filter can remove salt and pepper noise effectively meanwhile protect image details well thus getting better filtering performance compared with Traditional Median (TM) filter and other improved Switching Median (SM) filters for laser image.
7 citations
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...al [16], presents a Novel Adaptive Switching Median (NASM) filter that effectively handles the salt and pepper noisy image and preserves the image details as well....
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01 Jan 2016
TL;DR: The proposed method uses supervised learning capability of back-propagation neural network to remove the salt and pepper noise in first phase and adaptive median filter is used to enhance the image quality in second phase to overcomes all drawbacks of conventional median filtering.
Abstract: In this paper an efficient yet simple approach of salt and pepper noise removal based on back propagation neural network and adaptive median filtering has been suggested. The proposed method uses supervised learning capability of back-propagation neural network to remove the salt and pepper noise in first phase and adaptive median filter is used to enhance the image quality in second phase. It overcomes all drawbacks of conventional median filtering by preserving the fine details. Experimental results show that the algorithm performs better than neural network based model & other conventional filtering mechanisms. Performance is exceptionally good even for high density noised images.
7 citations
"An Efficient Image Denoising Approa..." refers background in this paper
...al in [11], is developed a hybrid approach that combines the back propagation neural network and adaptive median filtering in order to remove the salt and pepper noise and improve the image quality....
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01 Nov 2013
TL;DR: A trilateral filter is proposed which incorporates a third weighting function based on the rank order information of pixel values into the bilateral filter which removes impulsive noise and preserves edges of the objects in an image.
Abstract: The bilateral filter can remove Gaussian noise while preserving edges of the objects in an image. However the bilateral filter can not remove impulsive noise due to its edge preservation property. Therefore some robust bilateral filters have been proposed in order to also deal with impulsive noise. To make the bilateral filter more robust, this paper proposes a trilateral filter which incorporates a third weighting function based on the rank order information of pixel values into the bilateral filter. The effectiveness of the proposed method is verified in comparison with other conventional methods in experiments using the natural digital images corrupted by mixed Gaussian and impulsive noise.
6 citations
"An Efficient Image Denoising Approa..." refers methods in this paper
...al [8], use the rank order statistics filter to improve the quality of image which is corrupted due to impulse noise and is compared with traditional methods....
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TL;DR: A new technique for detecting the high density impulse noise from corrupted images using Fuzzy C-means algorithm which significantly outperforms existing well-known techniques and preserves more image details in high noise environment.
Abstract: A new technique for detecting the high density impulse noise from corrupted images using Fuzzy C-means algorithm is proposed. The algorithm is iterative in nature and preserves more image details in high noise environment. Fuzzy C-means is initially used to cluster the image data. The application of Fuzzy C-means algorithm in the detection phase provides an optimum classification of noisy data and uncorrupted image data so that the pictorial information remains well preserved. Experimental results show that the proposed algorithm significantly outperforms existing well-known techniques. Results show that with the increase in percentage of noise density, the performance of the algorithm is not degraded. Furthermore, the varying window size in the two detection stages provides more efficient results in terms of low false alarm rate and miss detection rate. The simple structure of the algorithm to detect impulse noise makes it useful for various applications like satellite imaging, remote sensing, medical imaging diagnosis and military survillance. After the efficient detection of noise, the existing filtering techniques can be used for the removal of noise.
6 citations
"An Efficient Image Denoising Approa..." refers methods in this paper
...In [3], an efficient method for detecting the impulse noise was developed....
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