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Image Descriptors and Features
Published in Manas Kamal Bhuyan, Computer Vision and Image Processing, 2019
The concept of Saliency saliency is employed to extract robust and relevant features [122]. In this approach, some of the regions of an image can be simultaneously unpredictable in some feature and scale-space, and these regions may be considered salient. Saliency is defined as the most prominent part of an image. Saliency model indicates what actually attracts the attention. The outputs of such models are called saliency maps. A saliency map refers to visually dominant locations and these pieces of information are topographically represented in the input image. So, a saliency map image shows unique quality of each and every pixel of an image. The saliency map simplifies and changes the representation of an image. This simplification or representation makes an image more meaningful and easier to analyze. An image can have more than one salient area, and one region may be more salient than the others.
Literature Survey on Recent Methods for 2D to 3D Video Conversion
Published in Ling Guan, Yifeng He, Sun-Yuan Kung, Multimedia Image and Video Processing, 2012
Raymond Phan, Richard Rzeszutek, Dimitrios Androutsos
Kim et al. [58] formulate a method that is based on visual attention analysis. Essentially, a saliency map is created where objects that are of importance and attract the viewer visually are given a higher value, than those that do not attract any attention. A five-feature pyramidal scheme, consisting of color, luminance, orientation, texture, and motion, is considered. Next, the saliency map of each of these features is computed in another pyramidal scheme, and is thus fused to produce a final visual attention map. The visual attention map is thus used to determine what the relative depth of the pixels should be, as pixels of interest should be deemed closer, than pixels that are not as interesting.
Adjusted-Purpose Watermarking
Published in Frank Y. Shih, Digital Watermarking and Steganography: Fundamentals and Techniques, 2017
where I is an input image, FT denotes the Fourier transform, “phase” means the phase spectrum, j is −1, and IFT denotes the inverse Fourier transform. For simplicity, the saliency map can be obtained by using a blurring filter—for example, a Gaussian filter or average filter.
An Ontology-based Knowledge Mining Model for Effective Exploitation of Agro Information
Published in IETE Journal of Research, 2022
E. Murali, S. Margret Anouncia
Similarly, Michelon et al. [22] developed a web application called AgDataBox for the control and management of agriculture fields. The data obtained from different sources, such as soil sample data, georeferenced images, precipitation, field operations, and thematic map, are taken as input. As a result, the thematic map can help toward the correct interpretation to fertilizer application at the right place and in the necessary amount to increase the productive potential in the field. Li et al. [23] proposed a novel method for recognizing crop plant in a field with weed. Visual features, such as color, intensity, and orientation, are extracted and combined to generate a saliency map. The experiment results demonstrate that the proposed method accurately segment crop plant from a weedy background in real-time.
Singular value decomposition and saliency - map based image fusion for visible and infrared images
Published in International Journal of Image and Data Fusion, 2022
C. Rajakumar, S. Satheeskumaran
The human visual system is more attractive to salient regions of the image than any other part of the image. The visual saliency map is a technique in which significant regions or salient parts of an image or human being or objects are highlighted. A viewer receives much attention from an object having good contrast than other objects of an image. To integrate information and complimentary information into fused images, the saliency map is introduced. Since the detail layer carries small-scale variations, boosting of detail layers is done by transferring information and complementary information into the detail layer. By including the saliency map and weight map, it is possible to integrate information into detail layers. Figure 3 describes the procedural steps involved in the construction of a saliency map from infrared images. Based on the above-said procedure, the construction of the saliency map is also possible for visible images.
Image Aesthetics Assessment Based on Multi-stream CNN Architecture and Saliency Features
Published in Applied Artificial Intelligence, 2021
Hironori Takimoto, Fumiya Omori, Akihiro Kanagawa
The visual saliency map is a topographically arranged map that represents the visual saliency of a corresponding visual scene. Visual saliency is defined as an estimation of how likely a given region is to attract human visual attention, and there is substantial evidence indicating a correlation between visual attention and saliency maps. It is expected that visual saliency estimation is applied when evaluating prominence in the design of sales promotion tools, public signboards, and so on.