2D Image data approximation using Savitzky Golay filter &amp;#x2014; Smoothing and differencing

Gowri, B.; Hariharan, Vishnu; Thara, S; Sowmya, V.; Kumar, Santosh; Soman, K P

doi:10.1109/imac4s.2013.6526438

Cited by 13 publications

(8 citation statements)

References 7 publications

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“…Savitzky-Golay Filters (S G Filters) have been used widely in the field of analytical chemistry. As per observations stated in [2] S G filters have exceptionally good properties in preserving edges. An approach based on S G filter-based smoothing used for the purpose of Optical Character Recognition (OCR) is also presented in [2].…”

Section: Savitzky-golay Filteringsupporting

confidence: 56%

“…As per observations stated in [2] S G filters have exceptionally good properties in preserving edges. An approach based on S G filter-based smoothing used for the purpose of Optical Character Recognition (OCR) is also presented in [2]. Consider a 2-D image, a and b represent the rows and the column indexes of each of the pixels and the value of the pixels represent the intensity.…”

Section: Savitzky-golay Filteringsupporting

confidence: 56%

“…This process thus becomes quiet lengthy and time consuming. This work similar to the case of bilateral filter-based compositing [1] but here we adopt the use of parametric filters specifically the Savitzky-Golay filter (S G filter) which is an edge preserving filter [2]. The filtered image stacks are used to generate weights to the input image stack and we perform the traditional alpha blending [3] which gives us the fused LDR image.…”

Section: Introductionmentioning

confidence: 99%

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Savitzky–Golay Filtering-Based Fusion of Multiple Exposure Images for High Dynamic Range Imaging

Ramakrishnan

Pete

2021

SN COMPUT. SCI.

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The problem of compositing multiple exposure images has attracted lots of researchers, over the past years. It all began with the problem of High Dynamic Range (HDR) imaging, for capturing scenes with vast differences in their dynamic range. Fine details in all the areas in these scenes cannot be captured with one single exposure setting of the camera aperture. This leads to multiple exposure images with each image containing accurate representation of different regions dimly lit, well lit and brightly lit in the scenes. One can make a combined HDR image out of these multiple exposure shots. This combination of multiple exposure shots leads to an image of a higher dynamic range in a different image format which cannot be represented in the traditional Low Dynamic Range (LDR) formats. Moreover HDR images cannot be displayed in traditional display devices suitable for LDR. So these images have to undergo a process called as tone mapping for further converting them to be suitable enough to be represented on usual LDR displays. An approach based on Savitzky-Golay parametric filtering which preserves edges, is proposed which uses filtered multiple exposure images to generate the alpha matte coefficients required for fusing the input multiple exposure set. The coefficients generated in the proposed approach helps in retaining the weak edges and the fine textures which are lost as a result of the under and over exposures. The proposed approach is similar in nature to the bilateral filter-based compositing approach for multiple exposure images in the literature but it is novel, in exploring the possibility of compositing using a parametric filtering approach. The proposed approach performs the fusion in the LDR domain and the fused output can also be displayed using standard LDR image formats on standard LDR displays. A brief comparison of the results generated by the proposed method and various other approaches, including the traditional exposure fusion, tone mapping-based techniques and bilateral filter-based approach is presented where in the proposed method compares well and fares better in majority of the test cases.

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Section: Savitzky-golay Filteringsupporting

confidence: 56%

Section: Savitzky-golay Filteringsupporting

confidence: 56%

Section: Introductionmentioning

confidence: 99%

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Savitzky–Golay Filtering-Based Fusion of Multiple Exposure Images for High Dynamic Range Imaging

Ramakrishnan

Pete

2021

SN COMPUT. SCI.

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“…The dead zone affects the control signal within -0. 15 An SGF of polynomial order equal to 4 and of frame size equal to 61 was used both for smoothing and for numerical differentiation in a noisy environment. The sample period was set to 0.01 s as the quasi-continuous implementation of the controllers was carried out.…”

Section: Case Study Experimental Resultsmentioning

confidence: 99%

“…The SGF is applied to estimate the firstorder derivative of the controlled output, and it is next included in (1). More detailed information about the SGF is given in [14] and [15]. (3) using (2) and introducing the estimation error…”

Section: Introductionmentioning

confidence: 99%

Model-free tuning solution for sliding mode control of servo systems

Precup

Rădac

Dragoş

et al. 2014

2014 IEEE International Systems Conference Proceedings

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This paper suggests a model-free tuning solution for a sliding mode control system (SMCS) structure dedicated to servo systems. The new SMCS structure is viewed in the framework of reference trajectory tracking using a first-order nonlinear dynamic system as a local approximation of the process model. The sliding mode control signal augments the control signal specific to a model-free PI control system (CS) structure in order to compensate for the estimation errors which affect the systematic design and performance. The derivatives in the local approximation of the process model are estimated numerically using a Savitzky-Golay filter to carry out both differentiation and smoothing. A simple design approach is proposed for the SMCS structure. The real-time experimental results concerning the speed control of a laboratory nonlinear DC servo system prove the performance improvement of the SMCS structure against a model-free PI CS structure.

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Human Body Parts Tracking from Pressure Data: Toward Effective Pressure Injury Assessment

Lastre-Dominguez

Hajari

et al. 2021

Lecture Notes in Computer Science

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2D Image data approximation using Savitzky Golay filter — Smoothing and differencing

Cited by 13 publications

References 7 publications

Savitzky–Golay Filtering-Based Fusion of Multiple Exposure Images for High Dynamic Range Imaging

Savitzky–Golay Filtering-Based Fusion of Multiple Exposure Images for High Dynamic Range Imaging

Model-free tuning solution for sliding mode control of servo systems

Human Body Parts Tracking from Pressure Data: Toward Effective Pressure Injury Assessment

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