imageprocessing related to noise suppression may entail partial distortion of useful visual information caused by filtering. Preservation of contours and texture details in the process of image denoising is one of th...
imageprocessing related to noise suppression may entail partial distortion of useful visual information caused by filtering. Preservation of contours and texture details in the process of image denoising is one of the important problems of computer vision. Recent years deep neural networks are widely applied in the tasks of noise suppression and signal recovering. However, neural networks are subjects to spectral bias towards low-frequency components. It results in blurring of contours and local high-frequency details after filtration. We propose loss function based on using high-frequency information of wavelet representation of images during network training to solve the problem. Our experiments demonstrate that this approach improves results of filtration in terms of signal to noise ratio and structural similarity index.
Discrete wavelet Transformation based watermarking algorithm gives robust, secure and strong results in non-blind and semi blind applications. High coefficients are selected in wavelet transform and binary image embed...
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ISBN:
(数字)9781665469487
ISBN:
(纸本)9781665469487
Discrete wavelet Transformation based watermarking algorithm gives robust, secure and strong results in non-blind and semi blind applications. High coefficients are selected in wavelet transform and binary image embedded into cover image as a watermark using secret key. Most of embedding algorithms use scaling factor a which is selected by try and use method. In this work, we use flexible scaling factor in different bands of the wavelet and also 8x8 blocks of the cover image to improve performance of the watermarking. Experimental results show that block and flexible scaling factor base wavelet watermarking gives better peak signal-to-noise ratio (PSNR) values in Lena, Barbara, peppers and cameraman images. In addition to that, extracted logo has very high similarity ratio (SR) if compared to other wavelet algorithms. Proposed algorithm is resist against the all common type of attacks.
The correlation of the wavelet shape and the characteristic ECG section has been confirmed, and wavelets for the identification of P-, R-, and T waves have been experimentally established. An algorithm for identifying...
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ISBN:
(数字)9798331518752
ISBN:
(纸本)9798331518769
The correlation of the wavelet shape and the characteristic ECG section has been confirmed, and wavelets for the identification of P-, R-, and T waves have been experimentally established. An algorithm for identifying R waves in an ECG has been developed and its operability has been verified. Using the algorithm developed, a graph of the dynamics of the heartbeat period is plotted as a function of time (period number). To identify the P and T waves, the waveletimage of the real ECG is constructed, and the presence of distortion of the shape of this image due to the influence of QRS complex and neighboring waves is established. Computer removal (filtering) of QRS complexes from the ECG is carried out, waveletimage of the remaining part is calculated. The possibility of determining the positions of the maximum P- and T-waves has been established from the waveletimage of the filtered ECG. The theoretical and practical value of this study consists in a new direction of wavelet analysis of cardiac signals, by successively applying several wavelets of a special form, to identify characteristic sections of the ECG in order to improve diagnostics. The proposed method also assumes intermediate filtering of the identified sections when moving from wavelet to wavelet. The development was carried out within the framework of computer generation of arrays of digital functions of the state of the heart, suitable for training artificial intelligence systems, and diagnostics using such systems. The practical results obtained can be applied in the development of a digital expert diagnostic system or a specific technical device.
image is an important information-bearing medium with many important attributes. If the image data is released directly, personal privacy will be compromised. This paper aims at how to use the method of differential p...
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ISBN:
(纸本)9783030967727;9783030967710
image is an important information-bearing medium with many important attributes. If the image data is released directly, personal privacy will be compromised. This paper aims at how to use the method of differential privacy to protect the privacy of image data and make the image data have high usability. In this paper, a WIP method based on wavelet change is proposed. Firstly, wavelet transform is used to compress the image. Then, noise is added to the main features after transformation to obtain the published image satisfying the differential privacy. It solves the problem of low usability of large images and the problem that Fourier transform cannot deal with abrupt signal. Experimental results show that compared with similar methods in the frequency domain, the denoised image obtained by the proposed WIP method is more distinguishable and the information entropy is closer to the original image. The accuracy is 10% higher than other methods. Compared with other frequency-domain methods for image differential privacy protection, the proposed WIP method has higher usability and robustness.
With the innovation and progress of data analysis, human action recognition has become a significant research direction with broad applications in many situations. We propose a skeleton temporal graph (STG) based on g...
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Automatic epileptic seizure prediction (AESP) is a challenge in epileptology since it has the potential to improve seizure incidence control while also providing a better understanding of seizure origin. We created a ...
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Hyperspectral (HS) image has rich spectral information content, which facilitates multiple applications including remote sensing. Due to the big data size of the HS image, compression is a required process for the eff...
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ISBN:
(纸本)9781665476478
Hyperspectral (HS) image has rich spectral information content, which facilitates multiple applications including remote sensing. Due to the big data size of the HS image, compression is a required process for the efficiency of image storage and transmission. However, the complexity of the compression algorithms turns real-time compression into a very challenging task. A novel listless set partitioned hyperspectral image compression algorithm is proposed. The proposed compression algorithm uses zero block cube tree structure to exploit the inter and intra sub-band correlation to achieve the compression. From the result, it has been clear that the proposed compression algorithm has low coding complexity with at-par coding efficiency. Thus, it can be a suitable contender for low-resource hyperspectral image sensors.
In order to investigate the feasibility of acoustic emission phenomenon aroused by electromagnetic excitation in metal specimens, electromagnetic acoustic emission model based on COMSOL software was established. On th...
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In this research, we propose a neat dual-tampering detection approach to further retrieve the forged content of 1080p images. The recovering of actual information is derived from the low-frequency components of the se...
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ISBN:
(数字)9798350390759
ISBN:
(纸本)9798350390766
In this research, we propose a neat dual-tampering detection approach to further retrieve the forged content of 1080p images. The recovering of actual information is derived from the low-frequency components of the second-order wavelet. The procedure initiates with the segmentation of the image into a non-underlying section. To make better the quality of the recuperate image, a radially symmetrical mapping technique is employed to safeguard the recovery bits. The most notable bit-plane of each segment is utilized to generate the first component authentication key through the MD5 algorithm, while the second component authentication key is produced using SHA1 based on the recovered data. Subsequently, the watermarked image is formed by embedding the recovery bits and the dual authentication keys into the least significant bits of the original image. During the tampering detection phase, the calculated authentication keys are compared against the retrieved keys. Any discrepancies result in the block being classified as tampered. Following this, centrosymmetric mapping is applied to extract the low-frequency coefficients of the second-order wavelet for the purpose of image self-recovery. The inverse wavelet transform is then executed to restore the tampered regions with the recovery data, thereby finalizing the self-recovery process. Our experimental findings indicate that this approach yields enhanced recovery quality and more effectively conceals the embedded information.
In recent years, medical image fusion has emerged as a comprehensive analytical method that frequently employs various modification techniques. The objective of multi-modal medical image fusion is to enhance image qua...
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