Speed of Processing and Stimulus Complexity in Low-Frequency and High-Frequency Channels

Perception ◽  
1997 ◽  
Vol 26 (8) ◽  
pp. 1039-1045 ◽  
Author(s):  
Rainer Hoeger
Keyword(s):  
High Frequency ◽  
Target Identification ◽  
Low Frequency ◽  
Object Perception ◽  
Stimulus Complexity ◽  
Frequency Information ◽  
Intensity Changes ◽  
Low Pass ◽  
Frequency Components ◽  
High Level

Studies of the microgenesis of perception led to the hypothesis that global aspects of objects are processed faster than their details. If one starts with the assumption that low-frequency information of objects corresponds to the global, and high-frequency information to the local aspects, recognising objects should rely at first on information from the low-frequency channels and afterwards from that of the high-frequency channels. The priming paradigm provides a mean of investigating experimentally the temporal availability of low-frequency and high-frequency information in object perception. In the experiments subjects had to respond to target objects preceded either by related or by unrelated priming stimuli, which consisted of low-pass-filtered and high-pass-filtered versions of the objects. With the influence of stimulus complexity controlled, pictures of objects were chosen that varied in the number of intensity changes in the high-frequency components, with those of the low-frequency components kept constant. The exposure duration of each prime was varied between 40 and 100 ms. The results indicated that target identification only profits more from low-frequency than from high-frequency primes if the high-frequency information has a high level of complexity. If the number of intensity changes in the high-frequency components of the prime is low, target identification is most strongly facilitated. The results are discussed in terms of models which focus on organising principles at different scales.

On a Design of Narrowband FIR Low-Pass Filters

2011 ◽  
pp. 2882-2887
Author(s):  
Gordana Jovanovic Dolecek ◽  
Javier Diaz Carmona
Keyword(s):  
Impulse Response ◽  
High Frequency ◽  
Digital Filters ◽  
Stop Band ◽  
Low Frequency ◽  
Pass Band ◽  
Low Pass ◽  
Frequency Components ◽  
Band Pass ◽  
High Pass

Stearns and David (1996) states that “for many diverse applications, information is now most conveniently recorded, transmitted, and stored in digital form, and as a result, digital signal processing (DSP) has become an exceptionally important modern tool.” Typical operation in DSP is digital filtering. Frequency selective digital filter is used to pass desired frequency components in a signal without distortion and to attenuate other frequency components (Smith, 2002; White, 2000). The pass-band is defined as the frequency range allowed to pass through the filter. The frequency band that lies within the filter stop-band is blocked by the filter and therefore eliminated from the output signal. The range of frequencies between the pass-band and the stop-band is called the transition band and for this region no filter specification is given. Digital filters can be characterized either in terms of the frequency response or the impulse response (Diniz, da Silva & Netto, 2002). Depending on its frequency characteristic, a digital filter is either low-pass, high-pass, band-pass, or band-stop filters. A low-pass (LP) filter passes low frequency components to the output, while eliminating high-frequency components. Conversely, the high-pass (HP) filter passes all high-frequency components and rejects all low-frequency components. The band-pass (BP) filter blocks both low- and high-frequency components while passing the intermediate range. The band-stop (BS) filter eliminates the intermediate band of frequencies while passing both low- and high-frequency components. In terms of their impulse responses digital filters are either infinite impulse response (IIR) or finite impulse response (FIR) digital filters. Each of four types of filters (LP, HP, BP, and BS) can be designed as an FIR or an IIR filter (Ifeachor & Jervis, 2001; Mitra, 2005; Oppenheim & Schafer, 1999).

Heart rate and blood pressure variabilities during graded head-up tilt

1995 ◽  
Vol 78 (1) ◽  
pp. 212-216 ◽  
Author(s):  
S. Mukai ◽  
J. Hayano
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Tilt Angle ◽  
High Frequency ◽  
Low Frequency ◽  
Normal Subjects ◽  
Arterial Baroreflex ◽  
Frequency Components ◽  
Head Up Tilt ◽  
High Level

We investigated the responses of the frequency components of heart rate (HR) and blood pressure (BP) variabilities to progressive changes in autonomic activity induced by the graded head-up tilt technique in 12 normal subjects (age 19–27 yr) under the condition of frequency-controlled respiration (0.25 Hz). During low-level tilt (0–30 degrees), the R-R interval was unchanged and the amplitude of the high-frequency (HF; 0.25 Hz) component of HR variability showed only a slight insignificant decrease. The amplitude of the low-frequency (LF; 0.04–0.15 Hz) component of HR variability increased progressively as the angle increased (P < 0.05). During high-level tilt (30–90 degrees), the R-R interval and the HF amplitude of HR variability decreased progressively with tilt angle (P < 0.001 for both). The LF amplitude of HR variability peaked at a tilt angle of 30 degrees. The LF-to-HF ratio of HR variability and the LF amplitude of systolic and diastolic BP variabilities increased progressively as the tilt angle increased from 0 to 60 degrees (P < 0.001), although systolic and diastolic BPs were unchanged. These results suggest that mixed autonomic responses to orthostatic stress, which are thought to be mediated by both cardiopulmonary and arterial baroreflex mechanisms, can be distinguished by changes in the frequency components of HR and BP variabilities.

Frequency Modulated Empirical Mode Decomposition Method

2012 ◽  
Vol 433-440 ◽  
pp. 4776-4781
Author(s):  
Xin Zhang ◽  
Xiu Li Du
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Hilbert Huang Transform ◽  
Mode Decomposition ◽  
Empirical Mode Decomposition Method ◽  
Low Pass ◽  
Frequency Components ◽  
Band Pass ◽  
Stiffness And Damping ◽  
Mixing Problem

Frequency modulation procedure is proposed to overcome the mode-mixing problem associated with the EMD method when processing signals with closely spaced frequencies. This procedure also provides the flexibility to start the realization of IMFs either from the high frequency end as does the original EMD or from the low frequency end when the signal contains unwanted high frequency components. The EMD procedure, under the circumstances, may behave as high pass, low pass or band pass/stop filters. The proposed method, assisted by the Hilbert-Huang transform on the governing equations, identifies the instantaneous stiffness and damping coefficients as functions of vibration amplitude of a nonlinear system. The effectiveness of the proposed method is verified by numerical simulation.

scholarly journals Fusion of IR and Visual Images Based on Gaussian and Laplacian Decomposition Using Histogram Distributions and Edge Selection

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Seohyung Lee ◽  
Daeho Lee
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Experimental Results ◽  
Visual Images ◽  
Fusion Method ◽  
Large Magnitude ◽  
Frequency Information ◽  
Frequency Components

We propose a novel fusion method of IR (infrared) and visual images to combine distinct information from two sources. To decompose an image into its low and high frequency components, we use Gaussian and Laplacian decomposition. The strong high frequency information in the two sources can be easily fused by selecting the large magnitude of Laplacian images. The distinct low frequency information, however, is not as easily determined. As such, we use histogram distributions of the two sources. Therefore, experimental results show that the fused images can contain the dominant characteristics of both sources.

scholarly journals A Novel Approach for Transmission Line Protection Using Wavelet Transform and Neural Network

2011 ◽  
pp. 121-126
Author(s):  
Mrunalini M. Rao ◽  
P.M. Deoghare
Keyword(s):  
Neural Network ◽  
Wavelet Transform ◽  
Transmission Line ◽  
High Frequency ◽  
Low Frequency ◽  
Line Length ◽  
Frequency Information ◽  
Protection Scheme ◽  
Frequency Components ◽  
Transmission Line Protection

The two most important expected objectives of the transmission line protection are – 1) Differentiating the internal faults from external faults and 2) identifying exactly the fault type using one end data only. In conventional distance protection scheme only 80 percent of line length gets primary protection while for remaining 20 percent of line length a time delay is provided to avoid maloperation due to overreach in case of D.C. offset. In this new scheme a fault generated transients based protection method is introduced by which the whole line length gets primary protection by using the concept of bus capacitance. This scheme implements improved solution based on wavelet transform and self-organized neural network. The measured current and voltage signals are preprocessed first and then decomposed using wavelet multiresolution analysis to obtain the high frequency and low frequency information. The training patterns are formed based on high frequency signal components and the low frequency components of all three phase voltages and current. Zero sequence voltage and current are also used to identify faults involving grounds. The input sets formed based on the high frequency components are arranged as inputs of neural network-1, whose task is to indicate whether the fault is internal or external. The input sets formed based on the low frequency components are arranged as inputs of neural network- 2, whose task is indicate the type of fault. The new method uses both low and high frequency information of the fault signal to achieve an advanced transmission line protection scheme.

Simulations of high-resolution images of amorphous silicon films

1986 ◽  
Vol 44 ◽  
pp. 544-545
Author(s):  
G. Y. Fan ◽  
J. M. Cowley
Keyword(s):  
Electron Microscope ◽  
High Frequency ◽  
Fourier Transformation ◽  
Amorphous Materials ◽  
Low Frequency ◽  
Chromatic Aberration ◽  
Structure Information ◽  
Frequency Components ◽  
High Resolution Images ◽  
Spatial Frequency Spectrum

It is well known that the structure information on the specimen is not always faithfully transferred through the electron microscope. Firstly, the spatial frequency spectrum is modulated by the transfer function (TF) at the focal plane. Secondly, the spectrum suffers high frequency cut-off by the aperture (or effectively damping terms such as chromatic aberration). While these do not have essential effect on imaging crystal periodicity as long as the low order Bragg spots are inside the aperture, although the contrast may be reversed, they may change the appearance of images of amorphous materials completely. Because the spectrum of amorphous materials is continuous, modulation of it emphasizes some components while weakening others. Especially the cut-off of high frequency components, which contribute to amorphous image just as strongly as low frequency components can have a fundamental effect. This can be illustrated through computer simulation. Imaging of a whitenoise object with an electron microscope without TF limitation gives Fig. 1a, which is obtained by Fourier transformation of a constant amplitude combined with random phases generated by computer.

A Novel Adaptive PET/CT Image Fusion Algorithm

2019 ◽  
Vol 14 (7) ◽  
pp. 658-666
Author(s):  
Kai-jian Xia ◽  
Jian-qiang Wang ◽  
Jian Cai
Keyword(s):  
Lung Cancer ◽  
Image Fusion ◽  
High Frequency ◽  
Malignant Tumors ◽  
Low Frequency ◽  
Combination Method ◽  
Ct Image ◽  
Fusion Algorithm ◽  
Pet Ct ◽  
Frequency Components

Background: Lung cancer is one of the common malignant tumors. The successful diagnosis of lung cancer depends on the accuracy of the image obtained from medical imaging modalities. Objective: The fusion of CT and PET is combining the complimentary and redundant information both images and can increase the ease of perception. Since the existing fusion method sare not perfect enough, and the fusion effect remains to be improved, the paper proposes a novel method called adaptive PET/CT fusion for lung cancer in Piella framework. Methods: This algorithm firstly adopted the DTCWT to decompose the PET and CT images into different components, respectively. In accordance with the characteristics of low-frequency and high-frequency components and the features of PET and CT image, 5 membership functions are used as a combination method so as to determine the fusion weight for low-frequency components. In order to fuse different high-frequency components, we select the energy difference of decomposition coefficients as the match measure, and the local energy as the activity measure; in addition, the decision factor is also determined for the high-frequency components. Results: The proposed method is compared with some of the pixel-level spatial domain image fusion algorithms. The experimental results show that our proposed algorithm is feasible and effective. Conclusion: Our proposed algorithm can better retain and protrude the lesions edge information and the texture information of lesions in the image fusion.

Despeckling of Sar Images Using Shrinkage of Two-Dimensional Discrete Orthonormal S-Transform

2020 ◽  
pp. 2150023
Author(s):  
Priya R. Kamath ◽  
Kedarnath Senapati ◽  
P. Jidesh
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Relevant Information ◽  
Detection Algorithm ◽  
Two Dimensional ◽  
Sar Images ◽  
S Transform ◽  
Processing Step ◽  
Frequency Components ◽  
Shock Filter

Speckles are inherent to SAR. They hide and undermine several relevant information contained in the SAR images. In this paper, a despeckling algorithm using the shrinkage of two-dimensional discrete orthonormal S-transform (2D-DOST) coefficients in the transform domain along with shock filter is proposed. Also, an attempt has been made as a post-processing step to preserve the edges and other details while removing the speckle. The proposed strategy involves decomposing the SAR image into low and high-frequency components and processing them separately. A shock filter is used to smooth out the small variations in low-frequency components, and the high-frequency components are treated with a shrinkage of 2D-DOST coefficients. The edges, for enhancement, are detected using a ratio-based edge detection algorithm. The proposed method is tested, verified, and compared with some well-known models on C-band and X-band SAR images. A detailed experimental analysis is illustrated.

Research on Improvement Algorithm of Image Edge Detection

2014 ◽  
Vol 539 ◽  
pp. 141-145
Author(s):  
Shui Li Zhang
Keyword(s):  
Cognitive Psychology ◽  
Edge Detection ◽  
High Frequency ◽  
Detection Method ◽  
Low Frequency ◽  
Frequency Information ◽  
Image Edge Detection ◽  
Improvement Algorithm ◽  
Image Edge ◽  
Edge Detection Method

This paper presents new theorems Stevens edge detection method based on cognitive psychology on. Firstly, based on the number of the image is decomposed into high-frequency and low-frequency information, and the high-frequency information extracted by subtracting the maximum number of images to the image after the filter, then the amount of high frequency information into psychological cognitive psychology based on Stevenss theorem. The algorithm suppression refined edge after the non-minimum, applications Pillar K-means algorithm to extract image edge. Experimental results show that: the brightness of the image is converted to the amount of psychological edge can better unify under different brightness values.

scholarly journals Image compression based on classification coding of constant-pitched functions transformers

2021 ◽  
pp. 48-62
Author(s):  
Vladimir Barannik ◽  
Andrii Krasnorutsky ◽  
Sergii Shulgin ◽  
Valerii Yeroshenko ◽  
Yevhenii Sidchenko ◽  
...  
Keyword(s):  
Image Compression ◽  
Data Transmission ◽  
High Frequency ◽  
Orthogonal Transformation ◽  
Low Frequency ◽  
Information Delivery ◽  
Video Data ◽  
Arithmetic Coding ◽  
Video Images ◽  
Frequency Components

The subject of research in the article are the processes of video image processing using an orthogonal transformation for data transmission in information and telecommunication networks. The aim is to build a method of compression of video images while maintaining the efficiency of its delivery at a given informative probability. That will allow to provide a gain in the time of delivery of compressed video images, a necessary level of availability and authenticity at transfer of video data with preservation of strictly statistical regulations and the controlled loss of quality. Task: to study the known algorithms for selective processing of static video at the stage of approximation and statistical coding of the data based on JPEG-platform. The methods used are algorithm based on JPEG-platform, methods of approximation by orthogonal transformation of information blocks, arithmetic coding. It is a solution of scientific task-developed methods for reducing the computational complexity of transformations (compression and decompression) of static video images in the equipment for processing visual information signals, which will increase the efficiency of information delivery.The following results were obtained. The method of video image compression with preservation of the efficiency of its delivery at the set informative probability is developed. That will allow to fulfill the set requirements at the preservation of structural-statistical economy, providing a gain in time to bring compressed images based on the developed method, relative to known methods, on average up to 2 times. This gain is because with a slight difference in the compression ratio of highly saturated images compared to the JPEG-2000 method, for the developed method, the processing time will be less by at least 34%.Moreover, with the increase in the volume of transmitted images and the data transmission speed in the communication channel - the gain in the time of delivery for the developed method will increase. Here, the loss of quality of the compressed/restored image does not exceed 2% by RMS, or not worse than 45 dB by PSNR. What is unnoticeable to the human eye.Conclusions. The scientific novelty of the obtained results is as follows: for the first time the method of classification (separate) coding (compression) of high-frequency and low-frequency components of Walsh transformants of video images is offered and investigated, which allows to consider their different dynamic range and statistical redundancy reduced using arithmetic coding. This method will allow to ensure the necessary level of availability and authenticity when transmitting video data, while maintaining strict statistical statistics.Note that the proposed method fulfills the set tasks to increase the efficiency of information delivery. Simultaneously, the method for reducing the time complexity of the conversion of highly saturated video images using their representation by the transformants of the discrete Walsh transformation was further developed. It is substantiated that the perspective direction of improvement of methods of image compression is the application of orthogonal transformations on the basis of integer piecewise-constant functions, and methods of integer arithmetic coding of values of transformant transformations.It is substantiated that the joint use of Walsh transformation and arithmetic coding, which reduces the time of compression and recovery of images; reduces additional statistical redundancy. To further increase the degree of compression, a classification coding of low-frequency and high-frequency components of Walsh transformants is developed. It is shown that an additional reduction in statistical redundancy in the arrays of low-frequency components of Walsh transformants is achieved due to their difference in representation. Recommendations for the parameters of the compression method for which the lowest value of the total time of information delivery is provided are substantiated.

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