The concealment of data has emerged as an area of deep and wide interest in research that endeavours to conceal data in a covert and stealth manner, to avoid detection through the embedment of the secret data into cover images that appear inconspicuous. These cover images may be in the format of images or videos used for concealment of the messages, yet still retaining the quality visually. Over the past ten years, there have been numerous researches on varying steganographic methods related to images, that emphasised on payload and the quality of the image. Nevertheless, a compromise exists between the two indicators and to mediate a more favourable reconciliation for this duo is a daunting and problematic task. Additionally, the current techniques have not been successful in attaining more improved security caused by the non-encrypted data that only underwent the first layer of concealment through merely a straightforward embedment process of the secret data within the images, thus allowing the extraction of the concealed data to be quite simple for hostile entities. Hence, in the current study, the proposed scheme, we have improved the Bit Inverting Map method to narrow the gap of existing work. Our experimental results indicate that the proposed framework maintains a better balance between image visual quality and security, with relatively less computational and complexity, which assures its effectiveness compared to other state-of-the-art methods.
A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.
Landsat7 of Enhanced thematic mapper plus (ETM+) was launched on April 15, 1999. Four years later, images start degrading due to the scan line corrector (SLC). SLC is a malfunction that results in pixel gaps in images captured by the sensor of Landsat7. The pixel gap regions extend from about one pixel near the image center and reach up to about 14 pixels in width near the image edge. The shape of this loss is like a zigzag line; however, there are different studies about repairing these gaps. The challenge of all studies depends on retrieving inhomogeneous areas because the homogenous area can be retrieved quickly depending on the surrounding area. This research focuses on filling these gaps by utilizing pixels around them
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A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a
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عملية تغيير حجم الصورة في مجال معالجة الصور باستخدام التحويلات الهندسية بدون تغيير دقة الصورة تعرف ب image scaling او image resizing. عملية تغيير حجم الصورة لها تطبيقات واسعة في مجال الحاسوب والهاتف النقال والاجهزة الالكترونية الاخرى. يقترح هذا البحث طريقة لتغيير حجم الصورة باستخدام المعادلات الخاصة بمنحني Bezier وكيفية الحصول على افضل نتائج. تم استخدام Bezier curve في اعمال سابقة في مجالات مختلفة ولكن في هذا البحث تم استخد
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Many recent satellite image compression methods depends on removing the spectral and spatial redundancies within image only , such these methods known as intra-frame(image) coding such as predictive and transformed based techniques , but these contributions needs a hard work in order to improve the compression performance also most of them are applied on individual data. The other trend is to exploit the temporal redundancy between the successive satellite images captured for the same area from different views, different sensors, or at different times, which will be much correlated and removing this redundancy will improve the compression performance and this principle known as inter-frame(image) coding .In this paper, a latest powerful
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There is a great deal of systems dealing with image processing that are being used and developed on a daily basis. Those systems need the deployment of some basic operations such as detecting the Regions of Interest and matching those regions, in addition to the description of their properties. Those operations play a significant role in decision making which is necessary for the next operations depending on the assigned task. In order to accomplish those tasks, various algorithms have been introduced throughout years. One of the most popular algorithms is the Scale Invariant Feature Transform (SIFT). The efficiency of this algorithm is its performance in the process of detection and property description, and that is due to the fact that
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In this paper, we introduce a new digital authentication certification system to keep the classified documents' information safe. The proposed system is a steganography system divided into two subsystems, the first subsystem is responsible for embedding the information about the person, and it works in the main foundation that issues the documents, while the second subsystem is found in the beneficiary directorates to extract the true information of the person.
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Restoration is the main process in many applications. Restoring an original image from a damaged image is the foundation of the restoring operation, either blind or non-blind. One of the main challenges in the restoration process is to estimate the degradation parameters. The degradation parameters include Blurring Function (Point Spread Function, PSF) and Noise Function. The most common causes of image degradation are errors in transmission channels, defects in the optical system, inhomogeneous medium, relative motion between object and camera, etc. In our research, a novel algorithm was adopted based on Circular Hough Transform used to estimate the width (radius, sigma) of the Point Spread Function. This algorithm is based o
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The process of accurate localization of the basic components of human faces (i.e., eyebrows, eyes, nose, mouth, etc.) from images is an important step in face processing techniques like face tracking, facial expression recognition or face recognition. However, it is a challenging task due to the variations in scale, orientation, pose, facial expressions, partial occlusions and lighting conditions. In the current paper, a scheme includes the method of three-hierarchal stages for facial components extraction is presented; it works regardless of illumination variance. Adaptive linear contrast enhancement methods like gamma correction and contrast stretching are used to simulate the variance in light condition among images. As testing material
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As result of exposure in low light-level are images with only a small number of
photons. Only the pixels in which arrive the photopulse have an intensity value
different from zero. This paper presents an easy and fast procedure for simulating
low light-level images by taking a standard well illuminated image as a reference.
The images so obtained are composed by a few illuminated pixels on a dark
background. When the number of illuminated pixels is less than 0.01% of the total
pixels number it is difficult to identify the original object.