- 标题
- 摘要
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- 实验方案
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Objective Quality Assessment of Image Enhancement Methods in Digital Mammography - A Comparative Study
摘要： Mammography is the primary and most reliable technique for detection of breast cancer. Mammograms are examined for the presence of malignant masses and indirect signs of malignancy such as micro calcifications, architectural distortion and bilateral asymmetry. However, Mammograms are X-ray images taken with low radiation dosage which results in low contrast, noisy images. Also, malignancies in dense breast are difficult to detect due to opaque uniform background in mammograms. Hence, techniques for improving visual screening of mammograms are essential. Image enhancement techniques are used to improve the visual quality of the images. This paper presents the comparative study of different pre-processing techniques used for enhancement of mammograms in mini-MIAS data base. Performance of the image enhancement techniques is evaluated using objective image quality assessment techniques. They include simple statistical error metrics like PSNR and human visual system (HVS) feature based metrics such as SSIM, NCC, UIQI, and Discrete Entropy
关键词： Adaptive median filter,HE,Contrast stretching,Wavelet transforms,CLAHE
更新于2025-09-23 15:23:52
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Investigation of Remote Sensing Image Fusion Strategy Applying PCA to Wavelet Packet Analysis Based on IHS Transform
摘要： Further exploration of wavelet packet analysis (WPA) in the area of image fusion has been a hot topic. It is a strategy to combine WPA with such other transforms as intensity–hue–saturation (IHS), principle component analysis (PCA) for image fusion between the panchromatic (PAN) and the multispectral (MS) image. The paper puts forward a distinct fusion method. Its main idea can be stated as three steps. Firstly, intensity component is derived from IHS model of the image after an MS image is transformed from RGB to IHS. Secondly, intensity component and a matched PAN image are decomposed by WPA at the second scale, respectively. The innovational concept with two aspects is applying PCA theory to merge wavelet packet coefficients. One is to detect edge and produce self-adaptive weighted ratios for low-frequency band. The other is to yield another weighted coefficients for high-frequency bands based on standard deviation. Lastly, the new intensity component created by implementing inverse WPA, matching with hue and saturation reserved, makes up a color composition. A fused image is produced when carrying out transformation from IHS to RGB for the composition. It turns out that the presented fusion strategy is effective with experiments.
关键词： Intensity–hue–saturation (IHS),Image fusion,PCA-based fusion rule,Principle component analysis (PCA),Wavelet packet analysis (WPA)
更新于2025-09-23 15:23:52
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Performance Assessment of High Resolution Airborne Full Waveform LiDAR for Shallow River Bathymetry
摘要： We evaluate the performance of full waveform LiDAR decomposition algorithms with a high-resolution single band airborne LiDAR bathymetry system in shallow rivers. A continuous wavelet transformation (CWT) is proposed and applied in two fluvial environments, and the results are compared to existing echo retrieval methods. LiDAR water depths are also compared to independent field measurements. In both clear and turbid water, the CWT algorithm outperforms the other methods if only green LiDAR observations are available. However, both the definition of the water surface, and the turbidity of the water significantly influence the performance of the LiDAR bathymetry observations. The results suggest that there is no single best full waveform processing algorithm for all bathymetric situations. Overall, the optimal processing strategies resulted in a determination of water depths with a 6 cm mean at 14 cm standard deviation for clear water, and a 16 cm mean and 27 cm standard deviation in more turbid water.
关键词： bathymetry,full waveform,wavelet transformation,LiDAR
更新于2025-09-23 15:23:52
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Blind Noisy Image Quality Assessment Using Sub-Band Kurtosis
摘要： Noise that afflicts natural images, regardless of the source, generally disturbs the perception of image quality by introducing a high-frequency random element that, when severe, can mask image content. Except at very low levels, where it may play a purpose, it is annoying. There exist significant statistical differences between distortion-free natural images and noisy images that become evident upon comparing the empirical probability distribution histograms of their discrete wavelet transform (DWT) coefficients. The DWT coefficients of low- or no-noise natural images have leptokurtic, peaky distributions with heavy tails; while noisy images tend to be platykurtic with less peaky distributions and shallower tails. The sample kurtosis is a natural measure of the peakedness and tail weight of the distributions of random variables. Here, we study the efficacy of the sample kurtosis of image wavelet coefficients as a feature driving an extreme learning machine which learns to map kurtosis values into perceptual quality scores. The model is trained and tested on five types of noisy images, including additive white Gaussian noise, additive Gaussian color noise, impulse noise, masked noise, and high-frequency noise from the LIVE, CSIQ, TID2008, and TID2013 image quality databases. The experimental results show that the trained model has better quality evaluation performance on noisy images than existing blind noise assessment models, while also outperforming general-purpose blind and full-reference image quality assessment methods.
关键词： sub-band,discrete wavelet transform (DWT),extreme learning machine (ELM),kurtosis,Blind noisy image quality assessment
更新于2025-09-23 15:23:52
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A profile error evaluation method for freeform surface measured by sweep scanning on CMM
摘要： Coordinate measuring machines (CMMs) are widely used in evaluating the profile error of the freeform surfaces. Traditional trigger probes are inefficient at collecting large scale measurement sets. A CMM equipped with a sweep scanning probe dramatically improves the efficiency of inspection. However, the large scale data obtained by scanning is challenging for most existing profile error evaluation methods, which are based on iterative algorithms. This paper proposes an efficient and accurate method to evaluate the profile error of freeform surfaces. To simultaneously simplify the calculation and retain the accuracy of evaluation, a new method to extract key points from scanning data set is presented. First, the key points are defined as those measured points with regional outstanding deviations from the design surface. Second, wavelet decomposition is utilized to decompose the curves formed by the deviations of the measured points in the scanning data set, and the key points are extracted according to the decomposition results. In addition, the key points set, as a representation of the scanning data, are evaluated using Sequential Quadratic Programming (SQP) algorithm. Finally, a simulation example and an actual machined part are used to test the proposed evaluation method. The results prove that the proposed method is both accurate and efficient.
关键词： Key points extraction,Profile error evaluation,Freeform surface,Wavelet decomposition,Sweep scanning
更新于2025-09-23 15:23:52
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Wavelet Denoising of High-Bandwidth Nanopore and Ion-Channel Signals
摘要： Recent work has pushed the noise-limited bandwidths of solid-state nanopore conductance recordings to more than 5 MHz and of ion channel conductance recordings to more than 500 kHz through the use of integrated complementary metal-oxide-semiconductor (CMOS) integrated circuits. Despite the spectral spread of the pulse-like signals that characterize these recordings when a sinusoidal basis is employed, Bessel filters are commonly used to denoise these signals to acceptable signal-to-noise ratios (SNRs) at the cost of losing many of the faster temporal features. Here, we report improvements to the SNR that can be achieved using wavelet denoising instead of Bessel filtering. When combined with state-of-the-art high-bandwidth CMOS recording instrumentation, we can reduce baseline noise levels by over a factor of four compared to a 2.5-MHz Bessel filter while retaining transient properties in the signal comparable to this filter bandwidth. Similarly, for ion channel recordings, we achieve a temporal response better than a 100-kHz Bessel filter with a noise level comparable to that achievable with a 25-kHz Bessel filter. Improvements in SNR can be used to achieve robust statistical analyses of these recordings, which may provide important insights into nanopore translocation dynamics and mechanisms of ion channel function.
关键词： ion channel,Nanopore,CMOS,wavelet,denoise.,SNR
更新于2025-09-23 15:23:52
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On image restoration from random sampling noisy frequency data with regularization
摘要： Consider the image restoration using random sampling noisy frequency data by total variation regularization. By exploring image sparsity property under wavelet expansion, we establish an optimization model with two regularizing terms specifying image sparsity and edge preservation on the restored image. The choice strategy for the regularizing parameters is rigorously set up together with corresponding error estimate on the restored image. The cost functional with data-fitting in the frequency domain is minimized using the Bregman iteration scheme. By deriving the gradient of the cost functional explicitly, the minimizer of the cost functional at each Bregman step is also generated by an inner iteration process with Tikhonov regularization, which is implemented stably and efficiently due to the special structure of the regularizing iterative matrix. Numerical tests are given to show the validity of the proposed scheme.
关键词： Image restoration,iteration,numerics,total variation,wavelet sparsity,error estimate
更新于2025-09-23 15:23:52
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[IEEE 2018 IEEE 3rd International Conference on Signal and Image Processing (ICSIP) - Shenzhen, China (2018.7.13-2018.7.15)] 2018 IEEE 3rd International Conference on Signal and Image Processing (ICSIP) - A New Image Denoising Method Based on Wavelet Multi-scale Registration Fusion
摘要： Image denoising is an eternal research topic. In this paper, a new image denoising method based on wavelet multi-scale registration fusion is proposed to solve the problem that it is easy to lose the edge and texture details of the image in the denoising process. First of all, we can get multiple sets of wavelet coefficients by using different wavelet bases to decompose the same noisy image. Then, the obtained wavelet coefficients are processed by the improved wavelet threshold shrink to get multiple denoising images of the same noisy image. At last, we use the fusion registration algorithm proposed in this paper to fuse the edge feature of multiple denoising images to get the final denoising image. The experiments prove that this method not only can effectively overcome the pseudo gibbs phenomenon caused by the hard threshold method, but also can overcome the image distortion phenomenon caused by the soft threshold method. More importantly, compared with existing methods, this method can effectively preserve the edge detail and texture features of the image and the image has a better visual effect after fusion registration. Therefore, it has a better application value.
关键词： wavelet multi-scale registration fusion,wavelet transform,improved wavelet threshold shrink,image denoising
更新于2025-09-23 15:22:29
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[IEEE 2018 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) - Stuttgart, Germany (2018.11.20-2018.11.22)] 2018 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP) - Secure and Robust Color Image Watermarking for Copyright Protection Based on Lifting Wavelet Transform
摘要： This paper presents a secure and robust color image watermarking algorithm for copyright protection. This method uses lifting wavelet transform (LWT) to decompose both the host image and the watermark into different sub-bands and performs watermark embedding in the transform domain. A security key is introduced in the algorithm for security purpose. Two color images are used to test the performance of the proposed algorithm. Results show that the scheme not only has good imperceptibility and but also are robust to various geometric and image processing attacks.
关键词： image processing,watermarking,robust and secure,lifting wavelet transform
更新于2025-09-23 15:22:29
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[IEEE 2018 China International SAR Symposium (CISS) - Shanghai (2018.10.10-2018.10.12)] 2018 China International SAR Symposium (CISS) - A High Frequency Vibration Compensation Approach in Terahertz SAR Based on Wavelet Multi-Resolution Analysis
摘要： The use of terahertz wave in SAR imaging can solve the difficulties of frame rate and detection of slow moving targets in conventional SAR imaging. The most important difference between terahertz SAR (THz-SAR) and conventional SAR is the treatment on motion compensation. For reason that the wavelength of terahertz SAR is much shorter than that of conventional microwave SAR, the tiny vibration of SAR platform will blur SAR images, especially high frequency components. The high frequency vibration will result in paired echoes in SAR imaging, which can't be focused with traditional SAR imaging algorithms. Thus the vibration parameters can't be estimated precisely enough to construct the reference function to compensate the sinusoidal modulation phase. So we first get focused paired echoes in terahertz SAR imaging through Doppler keystone transform (DKT), then we propose a frequency estimation method based on wavelet multi-resolution analysis, along with parametric space projection method, to complete the high frequency vibration estimation of terahertz SAR. At last, the numerical tests using the point target echoes validate the proposed method.
关键词： synthetic aperture radar,high frequency vibration error,Terahertz,wavelet multi-resolution analysis,vibration estimation
更新于2025-09-23 15:22:29