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The term ‘steganography’ encapsulates the practice of secretly embedding data into digital mediums including video, image and audio files. Although steganography is often associated with nefarious activities, conceptually it asserts several characteristics that render it useful in contemporary security applications. Not just a mechanism for criminals to communicate secret information over a digital...
The paper examines an application of the gradient-based algorithm to image denoising with noise values being in the range of the available (non-noisy) pixel values. The analyzed image is considered to be sparse in the 2D-DCT domain. The presented algorithm is a generalization of the previous results on denoising images when the noisy pixels can be detected and eliminated using the L-statistics. The...
This paper presents a FPGA (Field Programmable Gate Array)-based remotely sensed imagery denoising method, named FPGA-based median filtering. The proposed method is capable of processing large volume data since it takes full advantages of FPGA hardware and abundant logic units. This paper first overviews the traditional median filtering algorithm, and then highlights the FPGA-based filtering, including...
The Euler number of a binary image is a very important topological property for image processing pattern recognition, and computer vision. This paper proposes an efficient run-based algorithm for Euler number computing. For calculating 8-neighbor runs, unlike the conventional run-based algorithm, which needs to record start points and end points of all runs, our algorithm only needs to record end...
SR-based denoising methods have shown promising performance in image denoising. However, Because of the degradation of the noisy image, conventional SR based denoising models may not be accurate enough for the reconstruction of a clean image. Therefore, to reduce the noise corruption, a novel adaptive sparse representation based SAR image despeckling algorithm is proposed in this paper, where the...
Safety inspection for high-rise structures should be done regularly for follow-up test. However, as it is very dangerous job and direct manual examination takes a lot of time and money, its correct diagnosis is difficult. In this paper, computer vision-based structural safety inspection system is proposed to be designed. The proposed system is an image recognition monitoring system through wireless...
After four years of development of the Image Processing On Line journal (IPOL), this article presents a first analysis and overview of its scientific and technical development. The main issues met and overcome from the beginning of the journal are described with a focus on the purpose of the journal to establish a state of the art on the main Image Processing topics. The evolution of the online demonstration...
SAR images have distinctive characteristics compared to optical images: speckle phenomenon produces strong fluctuations, and strong scatterers have radar signatures several orders of magnitude larger than others. We propose to use an image decomposition approach to account for these peculiarities. Several methods have been proposed in the field of image processing to decompose an image into components...
Cracks are the most requiring type of pavement distresses to detect and classify automatically. Due to its nature are easily absorbed by other types of pavement surface damages. Moreover, the diversity of pavement surface makes the image detection system requiring efficient computer algorithms. The paper presents the solutions tested on surface distress data which were collected automatically using...
Structured illumination microscopy (SIM) is one of the promising technique of super resolution microscopy. Super resolution image is reconstructed with twice as high resolution as conventional microscopy by illuminating patterned excitation light and analyzing multiple images. In this paper, I will review the principle of SIM, and discuss artifacts of the reconstructed image.
Testing of image processing applications is a challenging job especially, when evaluating the correctness of output image. Generally, output images are evaluated manually by visual inspection carried out by an expert tester, which is the main hindrance in automation of testing process. Recently, statistical and metamorphic testing approaches are presented to automate output evaluation of image processing...
Stochastic Resonance(SR) enhances the weak signal by using noise, providing a new way to process the weak signal in the strong noise background. This paper tries to give out a new way of image processing based on bistable Stochastic Resonance and Weiner Filtering. The image is firstly processed by bistable Stochastic Resonance. Then the output image is optimized by Weiner Filtering. The results are...
In this study, a filter which uses the Gaussian function and selects its variance according to local properties of image without user intervention has been designed in order to eliminate the noise. Consequently, a gradient adaptive image filter that estimates variance and creates different kernel for each pixel in image has been obtained.
The paper investigates a three stage filtering scheme, namely: 1) signal decomposition, 2) filtering and 3) signal reconstruction. If marginal rank order filtering is used in step 2, the derived filtering scheme generalizes the classical order statistics one. Based on this idea, a new family of nonlinear filters, called decomposition filters, is proposed and investigated. The most interesting feature...
We study the output variance of a class of nonlinear filters, called da-filters. In general, it is impossible to obtain an explicit expression of the output variance because of the implicit Input/Output relationship, except for α=1 (median filter), α=2 (mean filter) and α=∞ (midrange filter). In this paper, we develop a new approach to the computation of the filter output variance. It is based on...
In this paper we propose a new adaptive weighted dα filter. The filter is adaptive regarding noise amplitude distribution, orientation of structures and anisotropy measures. The filter coefficient are chosen according to structure orientation and anisotropy measures. α value is chosen according to the result of local noise distribution and anisotropy coefficient estimations. Some experimental results...
Ultra high definition television (UHDTV) has gradually entered our daily life. However, because of the large data of UHDTV, it is hard to render images in real time. We proposed an eye tracking based solution using the concept of uncrowned window from vision research. The theory of uncrowded window suggests that human vision can only effectively recognize objects inside a small window. Object features...
The massive volume of video and image data, compels them to be stored in a distributed file system. To process the data stored in the distributed file system, Google proposed a programming model named MapReduce. Existing methods of processing images held in such a distributed file system, requires whole image or a substantial portion of the image to be streamed every time a filter is applied. In this...
A novel approach for OH-PLIF image processing, namely conditioned level-set (CLS) method, is presented in this paper. The complete CLS method consists of raw image pre-processing, adaptive intensity shareholding for linearization, initial contour extraction, region-lock optimization and level set iteration. The successful application of this method to typical molecule diffusion flames demonstrates...
The implementation of analog adaptive median filters for image processing is presented. The adaptive median filter is based on transconductance comparators, which saturation current is adapted to act as a local weight operator. Transistor level simulations, using 1.2mm parameters, have shown excellent results in high removing incidence noise. An image with 249 × 209 corrupted with 35% salt and pepper...
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