A new approach for salt dome detection using a 3D multidirectional edge detector

Amin, Asjad; Mohamed, Deriche

doi:10.1007/s11770-015-0512-2

Cited by 64 publications

(22 citation statements)

References 5 publications

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“…Similarly, the trend of cost reduction will almost remains same for other image processing applications [4–8, 23–27] either implemented as parallel or sequential architecture. The [6] and [23] applications are comprised of four anti-quadrant symmetric filters and four non-quadrant symmetric filters for performing respective filtering tasks.…”

Section: Discussionmentioning

confidence: 98%

“…Firstly it provides the capability within a single design for efficiently implementing a wide range of filter types and secondly it offers a further cost reduction via resource sharing for implementing those image-processing applications which require multiple types of filters sequentially for performing diversified image processing tasks. The diversified filter requirement for different applications ranges from biomedical [4, 5, 22, 23], computer vision [6, 24], surveillance and navigation [7, 25], industrial [26, 27] to geophysics [8] etc. In contrast to our proposed versatile framework, the previously reported structurally optimized designs such as [18] and [19] does not offer further cost reduction for such applications.…”

Section: Discussionmentioning

confidence: 99%

“…The [27] requires two anti-quadrant symmetric filters and two non-quadrant symmetric filters. The [8] requires three identity quadrant symmetric filter, six anti-quadrant symmetric filters and six non-quadrant symmetric filters. The [25] and [24] require an identity quadrant symmetric filter, two anti-quadrant symmetric filters and two non-quadrant symmetric filters.…”

Section: Discussionmentioning

confidence: 99%

“…In all of these applications, these 2D-filters (hereafter we call it filters) perform several important tasks such as enhancing fine details, suppressing unwanted noise, detecting edges, image fusion, compression, multi scale decomposition etc. [4–8]. The filtering operation can be performed either in spatial domain or frequency domain however since the images are inherently encoded in spatial domain therefore the spatial domain filtering is preferred [9, 10].…”

Section: Introductionmentioning

confidence: 99%

“…Consequently these optimized designs are compromised to support only those specific image processing applications which utilize filters present within the filter group being supported by them despite of providing an extended support for implementing multiple filter types for fulfilling the demand of advanced image processing applications. On the other hand, the diversified tasks of these image processing applications increasingly require different type of filters simultaneously for processing an input image to achieve their desired results rather than using a single filter type [4–8, 22–27]. These contradictory factors increase the implementation cost of complete image processing application proportionally by using above discussed optimized designs.…”

Section: Introductionmentioning

confidence: 99%

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A Low Cost Structurally Optimized Design for Diverse Filter Types

et al. 2016

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A wide range of image processing applications deploys two dimensional (2D)-filters for performing diversified tasks such as image enhancement, edge detection, noise suppression, multi scale decomposition and compression etc. All of these tasks require multiple type of 2D-filters simultaneously to acquire the desired results. The resource hungry conventional approach is not a viable option for implementing these computationally intensive 2D-filters especially in a resource constraint environment. Thus it calls for optimized solutions. Mostly the optimization of these filters are based on exploiting structural properties. A common shortcoming of all previously reported optimized approaches is their restricted applicability only for a specific filter type. These narrow scoped solutions completely disregard the versatility attribute of advanced image processing applications and in turn offset their effectiveness while implementing a complete application. This paper presents an efficient framework which exploits the structural properties of 2D-filters for effectually reducing its computational cost along with an added advantage of versatility for supporting diverse filter types. A composite symmetric filter structure is introduced which exploits the identities of quadrant and circular T-symmetries in two distinct filter regions simultaneously. These T-symmetries effectually reduce the number of filter coefficients and consequently its multipliers count. The proposed framework at the same time empowers this composite filter structure with additional capabilities of realizing all of its Ψ-symmetry based subtypes and also its special asymmetric filters case. The two-fold optimized framework thus reduces filter computational cost up to 75% as compared to the conventional approach as well as its versatility attribute not only supports diverse filter types but also offers further cost reduction via resource sharing for sequential implementation of diversified image processing applications especially in a constraint environment.

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