CN111738941B - Underwater image optimization method integrating light field and polarization information - Google Patents
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Abstract
The invention discloses an underwater image optimization method integrating light fields and polarization information, which comprises the following steps: collecting polarization diagrams of a target scene at different positions away from the target scene, wherein a plurality of polarization diagrams form a polarization diagram group; respectively restoring the polarization graphs at different positions to obtain polarization restored images at different positions; determining a target image in the polarization recovery image; optimizing the target image according to the polarized images at all different positions; the light field imaging technology and the polarization imaging technology are combined, multi-depth-of-field information of a scene is obtained in a one-time acquisition process, the information dimension obtained by single imaging is increased, the proposed polarization restoration algorithm is utilized to carry out initial restoration on each sub-depth-of-field image, and finally the light field correlation algorithm is utilized to carry out restoration fusion, so that the underwater imaging quality is improved.
Description
Technical Field
The invention relates to underwater image imaging, in particular to an underwater image optimization method integrating light fields and polarization information.
Background
In underwater imaging, the imaging quality is poor due to absorption of light by water and scattering of suspended particles. The current underwater image imaging method based on the atmospheric imaging model is not applicable to the environment under the water with low illumination and multiple suspended particles; the existing underwater image processing based on polarization information can improve the imaging quality, but it is difficult to distinguish forward and backward scattered light caused by suspended particles in the environment under water, so that the restored image is seriously distorted.
Disclosure of Invention
The invention provides an underwater image optimization method integrating light fields and polarization information, which aims to overcome the technical problems.
The invention discloses an underwater image optimization method integrating light fields and polarization information, which comprises the following steps:
collecting polarization diagrams of a target scene at different positions away from the target scene, wherein a plurality of polarization diagrams form a polarization diagram group;
respectively restoring the polarization graphs at different positions to obtain polarization restored images at different positions;
determining a target image in the polarization recovery image;
the target image is optimized from all the polarization images at different positions.
Further, the performing polarization diagram acquisition on the target scene at different positions from the target scene includes: adjusting the angle of a polaroid at a first position away from a target scene to acquire a plurality of polaroids from the target scene; and by analogy, at the N position away from the target scene, adjusting the angle of the polaroid to acquire a plurality of polaroids for the target scene.
Further, the restoring the polarization maps at different positions to obtain polarization restored images at different positions includes:
the polarization map group is labeled as follows using stokes vectors:
obtaining a total light intensity image, a horizontal and vertical direction intensity difference image and a 45 DEG and-45 DEG direction intensity difference image of an image scene at a current position, wherein S N0 Representing the total light intensity of the current position image scene S N1 Representing the intensity difference between the horizontal direction and the vertical direction of the current position, S N2 Representing the intensity difference in the 45 DEG and-45 DEG directions of the current position;
calculating the polarization degree of the image scene at the current position according to the total light intensity image, the intensity difference images in the horizontal direction and the vertical direction and the intensity difference images in the 45-degree directions of the image scene at the current position;
calculating a dark channel image of the total light intensity image according to the total light intensity image of the image scene at the current position;
dividing the dark channel image into four sub-images uniformly by adopting quadtree decomposition, and calculating the mean value and variance of the four sub-images;
determining a region only containing scattering effect of the dark channel image according to the difference value of the mean value and the variance of the sub-image, and determining the position of the brightest pixel point in the region only containing scattering effect;
determining a total light intensity image of an image scene at the current position, an intensity difference image in the horizontal direction and the vertical direction and an area containing only the scattering effect of the intensity difference image in the 45-degree direction and the-45-degree direction according to the area containing only the scattering effect of the dark channel image, and determining a back scattering light parameter at infinity according to the position of the brightest pixel point in the area containing only the scattering effect in the dark channel image;
calculating the polarization degree and the polarization angle of the backward scattered light according to the total light intensity image, the intensity difference images in the horizontal direction and the vertical direction and the areas only containing scattering effect of the intensity difference images in the 45 DEG and-45 DEG directions of the image scene of the current position;
calculating a back scattering light parameter according to the polarization degree and the polarization angle of the back scattering light and the polarization degree of the image scene at the current position;
and restoring the image scene of the current position according to the back scattering light parameter at infinity and the back scattering light parameter.
Further, the determining the area of the dark channel image only including the scattering effect according to the difference between the mean and the variance of the sub-images includes:
using the formula
Determining a region of the dark channel image containing only scattering effects, wherein theFor regions of the finally selected dark channel image which only contain scattering effects, the +.>Is the τ in the dark channel image * Sub-image block, τ * For image blocksSequence number τ * ，/>For the τ sub-image block in the dark channel image, said +.>Is the mean value of the tau sub-image block in the dark channel image, said +.>Is the variance of the tau sub-image block in the dark channel image, and tau is the image block serial number tau.
Further, determining the back-scattered light parameter at infinity according to the position of the brightest pixel point in the dark channel image only including the scattering effect area comprises:
using the formula
Determining a back-scattered light parameter at infinity, wherein B is N∞ (lambda) is back-scattered light at infinity, said S N0 (i * ,j * Lambda) is the position (i * ,j * ) In image S N0 A middle pixel value, said (i) * ,j * ) For the position of the brightest pixel point in the dark channel image only including the scattering effect region, theFor position (i, j) in image +.>A middle pixel value.
According to the invention, a light field imaging technology and a polarization imaging technology are combined, multi-depth-of-field information of a scene is obtained in a one-time acquisition process, the information dimension obtained by single imaging is increased, each sub-depth-of-field image is restored initially by using a proposed polarization restoration algorithm, and finally restoration and fusion are performed by using a light field correlation algorithm, so that the underwater imaging quality is improved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, a brief description will be given below of the drawings required for the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of underwater polarized optical imaging of the underwater image optimization method of the present invention which merges light field and polarized information;
fig. 2 is a schematic view of underwater polarized optical imaging by the underwater image optimization method integrating light field and polarized information.
FIG. 3 is a process of processing polarized images in the underwater image optimization method of the present invention that fuses light field and polarization information.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
FIG. 1 is a flow chart of the underwater image optimization method integrating light field and polarization information, which comprises the following processing steps:
collecting polarization diagrams of a target scene at different positions away from the target scene, wherein a plurality of polarization diagrams form a polarization diagram group;
respectively restoring the polarization graphs at different positions to obtain polarization restored images at different positions;
determining a target image in the polarization recovery image;
the target image is optimized from all the polarization images at different positions.
Further, the performing polarization diagram acquisition on the target scene at different positions from the target scene includes: adjusting the angle of a polaroid at a first position away from a target scene to acquire a plurality of polaroids from the target scene; and by analogy, at the N position away from the target scene, adjusting the angle of the polaroid to acquire a plurality of polaroids for the target scene.
In underwater imaging, the imaging quality is poor due to absorption of light by water and scattering of suspended particles, and as the imaging distance increases, these two effects become more pronounced, which causes difficulty in recovering the underwater image. According to the illustration of fig. 2, the camera receives light intensity from two aspects, one is signal light from the target reflection, which reaches the camera after being attenuated, namely:
D(i,j,λ,d)＝J(i,j,λ)·T(i,j,λ) (1)
the other is the back scattered light that is back scattered into the camera by the suspended particle scattering effect as it propagates, namely:
B(i,j,λ)＝(1-T(i,j,λ))·B ∞ (λ) (2)
the final camera imaging process can be expressed as
I(i,j,λ)＝D(i,j,λ)+B(i,j,λ)
＝J(i,j,λ)·T(i,j,λ)+(1-T(i,j,λ))·B ∞ (λ) (3)
Where (I, j) is a point in the image, I is the abscissa of the pixel in the image, j is the ordinate of the pixel in the image, d is the depth of field, λ is the wavelength of the light, λ e { red, green, blue } corresponds to the three color channels of the RGB image, B (I, j, λ) is the backscattered light, I (I, j, λ) is the image acquired by the camera, T (I, j, λ) =e -s(λ)d(i,j) Is a transmittance graph, B ∞ (λ) is backscattered light at infinity, D (i, J, λ) is signal light that reaches the camera after the target reflection is attenuated, and J (i, J, λ) is signal light that is not attenuated at all. By combining the formulas (1) - (3), the preparation method can be obtained,
therefore, from equation (4), it is known that B is to restore the image ∞ (lambda) and B (i, j, lambda) are two critical parameters that play a decisive role in the quality of the restoration of the image.
Further, as shown in fig. 3, the polarized image is processed by the following formula; because the traditional underwater image quality recovery based on polarization information adopts a fixed depth of field to shoot polarized images, accurate model parameter estimation values are difficult to obtain. In addition, human participation is needed in parameter estimation, which has a certain limitation in practical application.
The invention adopts different positions apart from a target scene to shoot polarized images of different initial angles, namely a multi-position polarized image group is obtained, so that the whole large light field information is acquired and recorded as:
(I 0 (0),I 0 (45),I 0 (90))，(I 1 (0),I 1 (45),I 1 (90))，......,(I N (0),I N (45),I N (90))，
the polarized image group of each sub-position is initially restored, and the polarized image group (I N (0),I N (45),I N (90) For the explanation of the restoration operation:
the restoring the polarization graphs at different positions respectively to obtain polarization restored images at different positions comprises the following steps: the polarization map group is labeled as follows using stokes vectors:
wherein S is N0 Representing the total light intensity of the scene at the current position S N1 Representing the intensity difference between the horizontal direction and the vertical direction of the current position, S N2 Representing the intensity difference in the 45 deg. and-45 deg. directions of the current position.
Obtaining a total light intensity image, a horizontal and vertical direction intensity difference image and a 45 DEG and-45 DEG direction intensity difference image of an image scene at a current position, wherein S N0 Representing the total light intensity of the current position image scene S N1 Representing the current bitSetting the intensity difference between the horizontal direction and the vertical direction, S N2 Representing the intensity difference in the 45 DEG and-45 DEG directions of the current position;
calculating the polarization degree of the image scene at the current position according to the total light intensity image, the intensity difference images in the horizontal direction and the vertical direction and the intensity difference images in the 45-degree directions of the image scene at the current position;
calculating a dark channel image of the total light intensity image according to the total light intensity image of the image scene at the current position;
dividing the dark channel image into four sub-images uniformly by adopting quadtree decomposition, and calculating the mean value and variance of the four sub-images;
determining a region only containing scattering effect of the dark channel image according to the difference value of the mean value and the variance of the sub-image, and determining the position of the brightest pixel point in the region only containing scattering effect;
determining a total light intensity image of an image scene at the current position, an intensity difference image in the horizontal direction and the vertical direction and an area containing only the scattering effect of the intensity difference image in the 45-degree direction and the-45-degree direction according to the area containing only the scattering effect of the dark channel image, and determining a back scattering light parameter at infinity according to the position of the brightest pixel point in the area containing only the scattering effect in the dark channel image;
calculating the polarization degree and the polarization angle of the backward scattered light according to the total light intensity image, the intensity difference images in the horizontal direction and the vertical direction and the areas only containing scattering effect of the intensity difference images in the 45 DEG and-45 DEG directions of the image scene of the current position;
calculating a back scattering light parameter according to the polarization degree and the polarization angle of the back scattering light and the polarization degree of the image scene at the current position;
and restoring the image scene of the current position according to the back scattering light parameter at infinity and the back scattering light parameter.
In particular, as the depth of field increases, the scattering effect increases and the image becomes increasingly blurred (i.e., the contrast is lower). The mean value representing the brightness of the image and the variance representing the contrast of the image can be used to determine the absenceIn the poor distant area, in order to avoid the influence of the highlight object in the target scene, the total light intensity image S is firstly displayed N0 Solving dark channel images:
then to the dark channel imagePerforming quadtree decomposition, calculating the mean M and variance S of each decomposed block region, subtracting variance from the mean, selecting the region with the largest difference according to formula (7), and repeating the steps until the final image block region +.>And determining the region as an infinity region containing only scattering effects based on the difference between the mean and variance of the sub-images, comprising using the formula:
determining a region of the dark channel image containing only scattering effects, wherein theFor regions of the finally selected dark channel image which only contain scattering effects, the +.>Is the τ in the dark channel image * Sub-image block, τ * For image block sequence number tau * ，/>For the τ sub-image block in the dark channel image, said +.>For the τ sub-image block in the dark channel imageMean value, said->Is the variance of the tau sub-image block in the dark channel image, and tau is the image block serial number tau.
Finding in Stokes vectorsThe area corresponding to the position is denoted as delta. The polarization degree and polarization angle of the backscattered light can thus be derived from equations (8) - (9), and |delta| represents the total number of pixels in this region.
In estimating key parameter B N∞ (lambda) and B N Most existing methods estimate (i, j, λ) by manually selecting a region without the target. However, the quality of the restored image is unstable due to the difference of manual operation. Because B is N∞ (lambda) and B N (i, j, λ) are parameters related to the backscattered light only, so that it is necessary to determine the area on the image that contains only the scattering effect. As the distance increases, different wavelengths are absorbed at a certain position, and the absorption effect disappears, so that only the scattering effect is contained in the region at infinity of the image.
Further, determining the back-scattered light parameter at infinity according to the position of the brightest pixel point in the dark channel image only including the scattering effect area comprises:
using the formula
Determining a back-scattered light parameter at infinity, wherein B is N∞ (lambda) is back-scattered light at infinity, said S N0 (i * ,j * Lambda) is the position (i * ,j * ) In image S N0 A middle pixel value, said (i) * ,j * ) For the position of the brightest pixel point in the area only containing scattering effect in the dark channel image, theFor position (i, j) in the image +.>A middle pixel value.
Estimating the backscattered light parameter B from the degree of polarization and the angle of polarization of the backscattered light, i.e. equations (8) - (9) N (i,j,λ)
Wherein,,
accordingly, the estimated parameter B N∞ (λ)，B N (i, J, λ) carrying into formula (4), recovering the degraded image J photographed at the nth position N (i,j,λ)。
Recovering degraded images at different positions by the method, and recording as J 0 (i,j,λ)，J 1 (i,j,λ)，...， J N (i, J, lambda) using the target image J (i, J, lambda) as a reference image, and respectively finding pixel points corresponding to the reference image in the images of other multiple positions; because of different shooting positions, the information such as intensity, color and the like reflected by the same object point is different, and the pixels of the same object point on the restored images with different distances are accumulated and averaged to be used as optimized pixel points of the object point in the target image, so that the quality of the target image is improved.
According to the invention, a light field imaging technology and a polarization imaging technology are combined, multi-depth-of-field information of a scene is obtained in a one-time acquisition process, the information dimension obtained by single imaging is increased, each sub-depth-of-field image is restored initially by using a proposed polarization restoration algorithm, and finally restoration and fusion are performed by using a light field correlation algorithm, so that the underwater imaging quality is improved.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (4)
1. An underwater image optimization method integrating light field and polarization information is characterized by comprising the following steps:
collecting polarization diagrams of a target scene at different positions away from the target scene, wherein a plurality of polarization diagrams form a polarization diagram group;
respectively restoring the polarization graphs at different positions to obtain polarization restored images at different positions;
the restoring the polarization graphs at different positions respectively to obtain polarization restored images at different positions comprises the following steps:
the polarization map group is labeled as follows using stokes vectors:
obtaining a total light intensity image, a horizontal and vertical direction intensity difference image and a 45 DEG and-45 DEG direction intensity difference image of an image scene at a current position, wherein S N0 Representing the total light intensity of the current position image scene S N1 Representing the intensity difference between the horizontal direction and the vertical direction of the current position, S N2 Representing the intensity difference in the 45 DEG and-45 DEG directions of the current position;
calculating the polarization degree of the image scene at the current position according to the total light intensity image, the intensity difference images in the horizontal direction and the vertical direction and the intensity difference images in the 45-degree directions of the image scene at the current position;
calculating a dark channel image of the total light intensity image according to the total light intensity image of the image scene at the current position;
dividing the dark channel image into four sub-images uniformly by adopting quadtree decomposition, and calculating the mean value and variance of the four sub-images;
determining a region only containing scattering effect of the dark channel image according to the difference value of the mean value and the variance of the sub-image, and determining the position of the brightest pixel point in the region only containing scattering effect;
determining a total light intensity image, a horizontal-direction and vertical-direction intensity difference image and a 45-degree and-45-degree-direction intensity difference image of the image scene at the current position according to the area only containing the scattering effect of the dark channel image, and determining back scattering light parameters at infinity according to the position of the brightest pixel point in the area only containing the scattering effect in the dark channel image;
calculating the polarization degree and the polarization angle of the backward scattered light according to the total light intensity image, the horizontal and vertical intensity difference images and the areas only containing scattering effect of the 45 DEG and-45 DEG intensity difference images of the image scene of the current position;
calculating a back scattering light parameter according to the polarization degree and the polarization angle of the back scattering light and the polarization degree of the image scene at the current position;
restoring the image scene at the current position according to the back scattering light parameter at infinity and the back scattering light parameter;
determining a target image in the polarization recovery image;
the target image is optimized from all the polarization images at different positions.
2. The method of claim 1, wherein the performing polarimetric image acquisition of the target scene at different locations from the target scene comprises: at a first position away from a target scene, adjusting the angle of a polaroid to acquire a plurality of polaroids for the target scene; and by analogy, at the N position away from the target scene, adjusting the angle of the polaroid to acquire a plurality of polaroids for the target scene.
3. The method of claim 1, wherein said determining the region of the dark channel image that contains only scattering effects based on the difference between the mean and variance of the sub-images comprises:
using the formula
Determining a region of the dark channel image containing only scattering effects, wherein theFor regions of the finally selected dark channel image which only contain scattering effects, the +.>Is the τ in the dark channel image * Sub-image block, τ * For image block sequence number tau * ，/>For the τ sub-image block in the dark channel image, said +.>Is the mean value of the tau sub-image block in the dark channel image, said +.>Is the variance of the tau sub-image block in the dark channel image, and tau is the image block serial number tau.
4. The method of claim 1, wherein determining the infinity back-scattered light parameter from the location of the brightest pixel point in the dark channel image including only the scattering effect area comprises:
using the formula
Determining a back-scattered light parameter at infinity, wherein B is N∞ (lambda) is back-scattered light at infinity, said S N0 (i * ,j * Lambda) is the position (i * ,j * ) In image S N0 A middle pixel value, said (i) * ,j * ) For the position of the brightest pixel point in the area only containing scattering effect in the dark channel image, theFor position (i, j) in the image +.>A middle pixel value.
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