NAA Mustafa, University of Sulaimani, Ms. c Thesis, 2010 - Cited by 4

The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing.  Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds.  This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by usin

Although the Wiener filtering is the optimal tradeoff of inverse filtering and noise smoothing, in the case when the blurring filter is singular, the Wiener filtering actually amplify the noise. This suggests that a denoising step is needed to remove the amplified noise .Wavelet-based denoising scheme provides a natural technique for this purpose .

                In this paper  a new image restoration scheme is proposed, the scheme contains two separate steps : Fourier-domain inverse filtering  and wavelet-domain image denoising. The first stage is Wiener filtering of the input image , the filtered image is inputted to adaptive threshold wavelet

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

رمت الدراسة التعرف بمستويات التفكير الهندسي لدى طلبة قسم الرياضيات في كلية التربية / ابن الهيثم - جامعة بغداد، ولتحقيق هدف الدراسة تم اعتماد مقياس الحربي(2003) المعد على البيئة السعودية ويتكون من (25)  فقرة موزعه على خمسة مستويات وهي (المستوى البصري ، التحليلي ، شبه الاستدلالي، الاستدلالي، المجرد وبلغت عينة الدراسة (206) طلاب من طلبة قسم الرياضيات في كلية التربية- ابن الهيثم بجامعة بغداد تم اختيارهم بالطريقة ال

هدف البحث الحالي الى قياس اسلوب الفكر المثالي عند طلبة قسم الكيمياء، كلية التربية للعلوم الصرفة ابن الهيثم. وقياس مدى الفكر المثالي حسب الصف الدراسي للمرحلة الجامعية. ولتحقيق هدفا البحث تم اتباع المنهج الوصفي. وتم تحديد مجتمع البحث بجميع طلبة قسم الكيمياء وللصفوف الاربعة ( الاولى ، الثانية، الثالثة، الرابعة) . وتم اختيار مجموعة من كل صف دراسي لتكون عينة للبحث الحالي. وتم اعداد اداة لقياس التفكير المثالي عند ع