Browsing by Author "Erer, I."

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DCT and Optimum Parameter Bilateral Filtering-Based Copy-Move Forgery Detection
(Institute of Electrical and Electronics Engineers Inc., 2021) Kiliç, U.; Kaplan, N.H.; Karabey Aksakalli, I.A.; Erer, I.
A digital image can be easily manipulated in today’s rapidly boosting technology. Among different types of image forgery methods, Copy-move forgery (CMF) is one of the most popular forgery methods in which a part of the image is copied and pasted into the same image or a different image. Therefore, the development of forgery detection methods has become a hot topic for both researchers and practitioners. In this study, a new CMF method combined with Discrete Cosine Transform (DCT) and optimum parameter Bilateral Filtering (OBF) is proposed to detect copied areas in a digital image. The visual and quantitative comparisons of the proposed hybrid method (DCT-OBF) have been made with traditional DCT based methods. The proposed method outperformed the former bilateral based method as well as the DCT based methods in terms of visual and quantitative analysis. Moreover, comparisons with conventional block-based methods have been carried out for different post-processing attacks such as image blurring and contrast adjustment. Quantitative comparisons demonstrate that the proposed method is better than the conventional block based methods, especially for post-processed images. For blurring post-processed images, the proposed method have provided higher Precision (18% improvement), F1 score (13% improvement), and Recall (5% improvement) rates than the former block based methods. © 2021 IEEE
Fast And Effective Clutter Reduction İn Ground Penetrating Radar Using Lifting Wavelet Transform
(Institute of Electrical and Electronics Engineers Inc., 2016) Karasakal, G.; Erer, I.; Kaplan, N.H.
Clutter, which is occurred by noise which has more intensive reflection than the buried objects such as noise of the transmitter and receiver antennas and the ground surface reflection interference, makes the identification of targets in Ground Penetrating Radar (GPR). Aim of this paper is to achieve a novel, more effective and faster clutter reduction method by using Lifting Wavelet Transform (LWT). LWT is applied on various scenarios and compared with Stationary Wavelet Transform (SWT) which is used very often in clutter and noise removal. In conclusion, LWT provides better and faster results. © 2016 IEEE.
Fast Weighted Least Squares Based Pansharpening
(Institute of Electrical and Electronics Engineers Inc., 2019) Kaplan, N.H.; Erer, I.
The fusion of high spatial resolution panchromatic (PAN) images with high spectral resolution multispectral (MS) images provides high resolution images in both spatial and spectral domains. In this work, a pansharpening method based on the fast weighted least squares (WLS) smoothing filter has been proposed. In this method, input PAN image has been decomposed into its approximation and detail sub bands by a multiscale scheme based on fast WLS filtering. The details extracted from the PAN image has been added proportionally the expanded MS image. The resulting images as well as evaluation metrics demonstrate that the proposed injection approach shows better performance than the traditional methods. © 2019 IEEE.
Fusion of Multifocus Images by Lattice Structures
(Academic Press Inc Elsevier Science, 2016) Kaplan, N. H.; Erer, I.; Ersoy, O.
Image fusion methods based on multiscale transform (MST) suffer from high computational load due to the use of fast Fourier transforms (ffts) in the lowpass and highpass filtering steps. Lifting wavelet scheme which is based on second generation wavelets has been proposed as a solution to this issue. Lifting Wavelet Transform (LWT) is composed of split, prediction and update operations all implemented in the spatial domain using multiplications and additions, thus computation time is highly reduced. Since image fusion performance benefits from undecimated transform, it has later been extended to Stationary Lifting Wavelet Transform (SLWT). In this paper, we propose to use the lattice filter for the MST analysis step. Lattice filter is composed of analysis and synthesis parts where simultaneous lowpass and highpass operations are performed in spatial domain with the help of additions/multiplications and delay operations, in a recursive structure which increases robustness to noise. Since the original filter is designed for the undecimated case, we have developed undecimated lattice structures, and applied them to the fusion of multifocus images. Fusion results and evaluation metrics show that the proposed method has better performance especially with noisy images while having similar computational load with LSWT based fusion method. (C) 2016 Elsevier Inc. All rights reserved.
Pansharpening Via Weighted Additive Wavelet Transform
(Institute of Electrical and Electronics Engineers Inc., 2016) Kaplan, N.H.; Erer, I.
In additive wavelet transform (AWT) based classical pansharpening methods, the details of the panchromatic (PAN) image added to the multispectral (MS) image directly or by weighting after the detail extraction. In this paper, the details will be weighted during the detail extraction process. The details of the PAN image will be obtained by a weighted additive wavelet transform (WAWT). In order to achieve this aim, the range parameter of WAWT will be optimized for every image. The results obtained by the proposed method are compared with the classical AWT method, the context based method (CBD), and the enhanced CBD (ECB) method. It is observed that the proposed injection approach has better performance than the conventional weighted detail injection schemes. © 2016 IEEE.
Remote Sensing Image Enhancement via Bilateral Filtering
(Institute of Electrical and Electronics Engineers Inc., 2017) Kaplan, N.H.; Erer, I.; Gulmus, N.
Remote sensing image enhancement methods have to increase the contrast and emphasize the edges, while preserving the color. In this study, an enhancement method based on bilateral filtering is proposed. We propose to extract the details of the image by a multiscale bilateral filter and add these details to the original image using a weighting scheme. Visual results and evaluation metrics show that the proposed method, enhance the image better than the former methods while it better preserves the original color information. © 2017 IEEE.
Remote Sensing Image Enhancement Via Robust Guided Filtering
(Institute of Electrical and Electronics Engineers Inc., 2019) Kaplan, N.H.; Erer, I.
Remote sensing image enhancement methods have to preserve the original reflectance values as possible as they can, whereas emphasising the edges and increasing the contrast. In this study, a remote sensing image enhancement method based on robust guided filtering is proposed. We propose a multiscale decomposition with the robust guided filtering to obtain the approximation and detail layers of the image. Then the extracted details are amplified and added to the approximation layer to obtain the enhanced image. Both visual and quantitative comparisons show that the proposed method has a better preservation capability than the former methods, as well as a better contrast improvement along-with edge enhancement. © 2019 IEEE.