Maximum entropy-based road shadow suppression method

A technology of maximum entropy and shadows, applied in image data processing, instruments, calculations, etc., can solve the problems of road area processing and incomplete elimination of shadows, and achieve the effect of suppressing shadows, simple principle, and strong robustness

Inactive Publication Date: 2015-07-29
SOUTHEAST UNIV
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Problems solved by technology

[0006] Purpose of the invention: This invention aims to solve the problems of incomplete elimination of shadows and easy removal of road areas in similar methods

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  • Maximum entropy-based road shadow suppression method
  • Maximum entropy-based road shadow suppression method
  • Maximum entropy-based road shadow suppression method

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Embodiment Construction

[0029] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0030] A method for suppressing road surface shadows based on maximum entropy disclosed in an embodiment of the present invention mainly includes the following steps:

[0031] 1. Image preprocessing

[0032] (1) Noise reduction processing

[0033] Here, bilateral filtering is used to denoise the image. Bilateral filtering is a nonlinear filtering method, which takes into account the spatial information and gray similarity of the image at the same time. Compared with other filtering methods, the...

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Abstract

The invention relates to a maximum entropy-based road shadow suppression method and belongs to the technical field of image processing. The maximum entropy-based road shadow suppression method is used for reducing interference of road shadow during road detection. For solving the problem that similar methods are not thorough in shadow suppression and are prone to eliminating effective road areas, the technical scheme of the maximum entropy-based road shadow suppression method comprises, firstly, transferring a colorful image into an HSV (hue, saturation and value) color space, and extracting the HSV feature (log (H / S), log (V / S)) of every pixel point; secondly, projecting the HSV features of all the pixel points in the HSV image into a one-dimensional space, calculating the entropy values of the HSV features in the one-dimensional space, changing the projection angle a to obtain the entropy values corresponding to different projection angles, and determining the projection angle am corresponding to the maximum entropy value; lastly, reconstructing the HSV image on the basis of the projection angle am, performing binarization and hole filling sequentially on the reconstructed image to obtain a shadow-suppressed road image. The maximum entropy-based road shadow suppression method is efficient, feasible and high in adaptability to different road conditions.

Description

technical field [0001] The invention relates to a road surface shadow suppression method based on maximum entropy in HSV space, and belongs to the technical field of digital image processing. Background technique [0002] Using digital image processing technology for road detection, the biggest challenge lies in the interference of road surrounding scenes and road shadows. The existing road shadow suppression methods can be roughly divided into two categories: the first method is to detect the shadow first, and then perform color compensation on the detected shadow according to the color characteristics around the shadow; the second method is to use a certain method The image is reconstructed to treat the road surface and the shadow as a whole at the same time, thereby indirectly suppressing the shadow. [0003] A typical representative of the first type of method is "Shadow detection and removal from remote sensing images using NDI and morphological operators" (Singh K K, ...

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Application Information

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IPC IPC(8): G06T5/00
Inventor 卢凯悦夏思宇
Owner SOUTHEAST UNIV
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