CN102722868B - Tone mapping method for high dynamic range image - Google Patents

Abstract

The invention discloses a tone mapping method for a high dynamic range image. The method comprises the following steps of: firstly, reading the high dynamic range image, and acquiring a log-domain brightness image of the high dynamic range image; secondly, estimating illumination components of the high dynamic range image by multi-scale weighted least squares (WLS) filtering to avoid the phenomenon of halo generated at a high light and shade contrast place; thirdly, recovering brightness components of the high dynamic range image by using a multi-scale Retinex method, eliminating the gray of a 1% part of each of two poles to prevent under-exposure and over-exposure, and adjusting the brightness degree of the image according to a self-adaptive adjustment function; and finally, recovering the color of the high dynamic range image by introducing an index control saturation method. The tone mapping method for the high dynamic range image is applicable to display and output of the high dynamic range image on low dynamic range equipment, generation of the halo can be avoided, and the displayed image has the characteristics of high contrast and good detail reproduction effect.

Description

A kind of high dynamic range image tone mapping method

Technical field

The invention belongs to digital image processing techniques field, for reproduce high dynamic range images on low-dynamic range display device, be specifically related to a kind of high dynamic range image tone mapping method.

Background technology

The brightness range of high dynamic range images is generally at 0.001cd/m ²to 100000cd/m ²between.Because high dynamic range images can be good at reproducing gray scale abundant in actual scene, produce effect true to nature, it is applied to the fields such as video display, computer game, military affairs, astronomy and medical science detection just more and more widely.With respect to the brightness range of high dynamic range images, the brightness range that many display devices (as CRT, LCD, projector etc.) can produce seems too narrow, and the brightness range producing as common CRT is approximately 1cd/m ²to 100cd/m ²therefore, use regular display to show that high dynamic range images there will be the unmatched problem of dynamic range.Therefore, need to adopt certain mode to compress the dynamic range of high dynamic range images, make it coupling output on the limited medium of dynamic range, this process is called tone mapping (tone mapping).

Recent domestic scholar has proposed many tone mapping methods, mainly can be divided into two classes: the 1) overall situation (Global) operator; 2) local (Local) operator.Overall situation operator only depends on the brightness value of pixel, and Local Operator not only relies on the brightness value of pixel, but also relevant with position and the neighborhood territory pixel brightness value of pixel.Local Operator, owing to having considered spatial neighborhood Pixel Information, can retain more image detail information and local contrast, thereby can obtain good mapping effect, becomes the emphasis of current concern.But Local Operator easily produces " halation (Halo) " phenomenon when processing high dynamic range images, affects display effect.

Summary of the invention

The object of this invention is to provide a kind of high dynamic range image tone mapping method, solved " halation " and the imperfect problem of display effect that in existing method, exist.

The technical solution used in the present invention is, a kind of high dynamic range image tone mapping method is implemented according to following steps:

Step 1, obtains the luminance picture L of high dynamic range images _in, and the formation log-domain luminance picture L that takes the logarithm, R wherein, G, B are respectively the red, green, blue color value of each pixel of high dynamic range images, and it is calculated as:

L _in＝0.299R+0.587G+0.114B，

L＝log(L _in+0.00001)；

Step 2, carries out multiple dimensioned WLS filtering to L, estimates multiple dimensioned illumination component L _k, k=1 wherein, 2 ..., to avoid comparison of light and shade strongly to locate " halation " phenomenon producing, it is expressed as:

L _k＝WLS(L,λ _k)，

Wherein operator WLS () represents to carry out WLS filtering, λ _krepresent scale factor, its value has determined illumination component image L _klevel and smooth degree, increase λ _k, will make level and smooth degree increase, conventionally can determine its value according to experiment situation;

Step 3, adopts multiple dimensioned Retinex method to recover the brightness composition of high dynamic range images, that is:

Wherein N represents yardstick number, ω _kfor the weight coefficient of different scale, and

Step 4, to R _lfetching number, obtains R ₁, that is: R ₁=exp (R _l);

Step 5, cancellation R ₁two extreme 1% gray level, prevents under-exposure and generation overexposure, and is normalized, and obtains R ₂, that is:

$R_2=\left\{\begin{array}{cc}0& R_1<m_s\\ \frac{R_1-m_s}{m_l-m_s}& m_s\&le;R_1<m_l\\ 1& R_1\&GreaterEqual;m_l\end{array}\right.,$

M wherein _sr ₁after middle pixel value sorts from small to large, 1% the corresponding R in pixel place ₁value; m _lr ₁after middle pixel value sorts from small to large, 99% the corresponding R in pixel place ₁value;

Step 6, adopts self-adaptation adjustment function to R ₂regulate, and its gray-scale value is mapped to the scope of [0,255], that is: $L_{\mathrm{out}}={\left(R_2\right)}^{\frac{\log \left(b\right)}{\log \left(0.5\right)}}\&times;255,$

Wherein, regulate parameter b can obtain the image of different bright-dark degrees, the span of b is [0.5,1.0];

Step 7, introduces index and controls saturation degree, adopts following computing formula, carries out color recovery, completes high dynamic range image tone mapping:

$\left\{\begin{array}{c}{R}_{\mathrm{out}}={\left(\frac{R}{L_{\mathrm{in}}}\right)}^s\&times;L_{\mathrm{out}}\\ G_{\mathrm{out}}={\left({\frac{G}{L}}_{\mathrm{in}}\right)}^s\&times;L_{\mathrm{in}}\\ B_{\mathrm{out}}={\left(\frac{B}{L}\right)}^s\&times;L_{\mathrm{out}}\end{array}\right.,$

Its Exponential s is for controlling saturation degree, R _out, G _out, B _outbe respectively the red, green, blue color value that high dynamic range images finally obtains after tone mapping.

The invention has the beneficial effects as follows, adopt multiple dimensioned WLS wave filter to estimate the illumination component of high dynamic range images, overcome preferably " halation " problem existing in tone mapping process; By removing two extreme 1% gray level and adopting self-adaptation adjustment function, make the image after tone mapping have the advantages that contrast is high, details display effect is good, can on low-dynamic range display device, can reproduce better high dynamic range images.

Accompanying drawing explanation

Fig. 1 is embodiment 1 high dynamic range images demonstrating after adopting the inventive method to process;

Fig. 2 is the high dynamic range images demonstrating after adopting the existing high dynamic range image tone mapping method based on Retinex to process;

Fig. 3 is that comparison diagram is amplified in the part at above-mentioned Fig. 1 black surround position and Fig. 2 black surround position.

Embodiment

Below by embodiment, the present invention is described in detail.

High dynamic range image tone mapping method of the present invention, according to following steps, implement:

Step 1, obtains the luminance picture L of high dynamic range images _in, and the formation log-domain luminance picture L that takes the logarithm, R wherein, G, B are respectively the red, green, blue color value of each pixel of high dynamic range images, and it is calculated as:

L _in＝0.299R+0.587G+0.114B，

L＝log(L _in+0.00001)；

Step 2, carries out multiple dimensioned WLS filtering to L, estimates multiple dimensioned illumination component L _k, k=1 wherein, 2 ..., to avoid comparison of light and shade strongly to locate " halation " phenomenon producing, it is expressed as:

L _k＝WLS(L,λ _k)，

Wherein operator WLS () represents to carry out WLS filtering, λ _krepresent scale factor, its value has determined illumination component image L _klevel and smooth degree, increase λ _k, will make level and smooth degree increase, conventionally according to experiment situation, determine its value.

For multiple dimensioned WLS filtering, it is specifically calculated as:

L _k＝(I+λ _kL _g) ^-1L，

Wherein, I is unit matrix, λ _kfor scale factor, L _gfor:

$L_g=D_x^T{A}_x{D}_x+D_y^T{A}_y{D}_y,$

D wherein _x, D _ybe respectively horizontal and vertical direction differential sampling parameter, T represents transpose of a matrix, A _x, A _ybe diagonal matrix, its diagonal entry is respectively a _x,p(L), a _y,p(L), it is calculated as:

$\left\{\begin{array}{c}{a}_{x,p}\left(L\right)={({\left|\frac{\&PartialD;l}{\&PartialD;x}\left(p\right)\right|}^{\mathrm{\&alpha;}}+\mathrm{\&epsiv;})}^{-1}\\ a_{y,p}\left(L\right)={({\left|\frac{\&PartialD;l}{\&PartialD;x}\left(p\right)\right|}^{\mathrm{\&alpha;}}+\mathrm{\&epsiv;})}^{-1}\end{array}\right.,$

Wherein parameter alpha is used for representing to control the sensitivity of smoothing process to image border, and span is 1.0-1.8; Parameter l=log (L+0.000001), constant ε value is 0.00001, is mainly in order to prevent that denominator from being zero situation appearance.

Step 3, adopts multiple dimensioned Retinex method to recover the brightness composition of high dynamic range images, that is:

N represents scale parameter, generally gets 3 yardsticks.

ω wherein _kfor the weight coefficient of different scale, and

Step 4, the R that step 3 is obtained _lfetching number, obtains R ₁, that is: R ₁=exp (R _l);

Step 5, cancellation R ₁two extreme 1% gray level, prevents under-exposure and generation overexposure, and is normalized, and obtains R ₂, that is:

$R_2=\left\{\begin{array}{cc}0& R_1<m_s\\ \frac{R_1-m_s}{m_l-m_s}& m_s\&le;R_1<m_l\\ 1& R_1\&GreaterEqual;m_l\end{array}\right.,$

Wherein, m _sr ₁after middle pixel value sorts from small to large, 1% the corresponding R in pixel place ₁value; m _lr ₁after middle pixel value sorts from small to large, 99% the corresponding R in pixel place ₁value;

Step 6, adopts self-adaptation adjustment function to R ₂regulate, and its gray-scale value is mapped to the scope of [0,255], that is: wherein, the numerical value of adjusting parameter b can obtain the image of different bright-dark degrees, and the span of b is [0.5,1.0];

Step 7, introduces index and controls saturation degree, adopts following computing formula, carries out color recovery:

$\left\{\begin{array}{c}{R}_{\mathrm{out}}={\left(\frac{R}{L_{\mathrm{in}}}\right)}^s\&times;L_{\mathrm{out}}\\ G_{\mathrm{out}}={\left({\frac{G}{L}}_{\mathrm{in}}\right)}^s\&times;L_{\mathrm{in}}\\ B_{\mathrm{out}}={\left(\frac{B}{L}\right)}^s\&times;L_{\mathrm{out}}\end{array}\right.,$ Complete high dynamic range image tone mapping,

Its Exponential s is for controlling saturation degree, R _out, G _out, B _outbe respectively the red, green, blue color value that high dynamic range images finally obtains after tone mapping.

Embodiment 1

High dynamic range image tone mapping method of the present invention, by following steps and design parameter, implement:

Step 1, reads high dynamic range images, the data of its floating type is converted to the data of the rgb format of integer, then calculates the luminance picture L of this high dynamic range images _in, and the formation log-domain luminance picture L that takes the logarithm, it is calculated as:

L _in＝0.299R+0.587G+0.114B，

L＝log(L _in+0.00001)，

Step 2, carries out multiple dimensioned WLS filtering to L, estimates multiple dimensioned illumination component L _k(k=1,2, L), to avoid comparison of light and shade strongly to locate " halation " phenomenon producing.It can be expressed as:

L _k＝WLS(L,λ _k)，

Wherein operator WLS () represents to carry out WLS filtering, λ _krepresent scale factor, its value has determined illumination component image L _klevel and smooth degree, increase λ _k, will make level and smooth degree increase, conventionally according to experiment situation, determine its value.In the present embodiment, adopt three yardsticks, i.e. k=1,2,3, get λ ₁=1, λ ₂=5, λ ₃=25.

For multiple dimensioned WLS filtering, it is specifically calculated as: L _k=(I+ λ _kl _g) ^-1l,

Wherein I is unit matrix, λ _kfor scale factor, L _gfor:

Wherein, D _x, D _ybe respectively horizontal and vertical direction differential sampling parameter, A _x, A _ybe diagonal matrix, its diagonal entry is respectively a _x,p(L), a _y,p(L), it is calculated as:

$\left\{\begin{array}{c}{a}_{x,p}\left(L\right)={({\left|\frac{\&PartialD;l}{\&PartialD;x}\left(p\right)\right|}^{\mathrm{\&alpha;}}+\mathrm{\&epsiv;})}^{-1}\\ a_{y,p}\left(L\right)={({\left|\frac{\&PartialD;l}{\&PartialD;x}\left(p\right)\right|}^{\mathrm{\&alpha;}}+\mathrm{\&epsiv;})}^{-1}\end{array}\right.,$ Wherein parameter alpha in the present embodiment, is got α=1.5.

Step 3, adopts multiple dimensioned Retinex method to recover the brightness composition of high dynamic range images, that is:

ω wherein _kfor the weight coefficient of different scale, and in the present embodiment, get 3 yardsticks, get accordingly ω ₁=0.25, ω ₂=0.5, ω ₃=0.25.Get

Step 4, to R _lfetching number, obtains R ₁, that is: R ₁=exp (R _l);

Step 5, cancellation R ₁two extreme 1% gray level, prevents under-exposure and generation overexposure, and is normalized, and obtains R ₂, that is:

$R_2=\left\{\begin{array}{cc}0& R_1<m_s\\ \frac{R_1-m_s}{m_l-m_s}& m_s\&le;R_1<m_l\\ 1& R_1\&GreaterEqual;m_l\end{array}\right.,$

M wherein _sr ₁after middle pixel value sorts from small to large, 1% the corresponding R in pixel place ₁value; m _lr ₁after middle pixel value sorts from small to large, 99% the corresponding R in pixel place ₁value;

Step 6, adopts self-adaptation adjustment function to R ₂regulate, and its gray-scale value is mapped to the scope of [0,255], that is: regulate parameter b in the present embodiment, get b=0.78.

Step 7, introduces index and controls saturation degree, adopts following computing formula, in the present embodiment, gets s=1/2.2.Carry out color recovery, can complete high dynamic range image tone mapping.

$\left\{\begin{array}{c}{R}_{\mathrm{out}}={\left(\frac{R}{L_{\mathrm{in}}}\right)}^s\&times;L_{\mathrm{out}}\\ G_{\mathrm{out}}={\left({\frac{G}{L}}_{\mathrm{in}}\right)}^s\&times;L_{\mathrm{in}}\\ B_{\mathrm{out}}={\left(\frac{B}{L}\right)}^s\&times;L_{\mathrm{out}}\end{array}\right.,$

Its Exponential s is for controlling saturation degree, R _out, G _out, B _outbe respectively the red, green, blue color value that high dynamic range images finally obtains after tone mapping.

Fig. 1 is the high dynamic range images showing after the embodiment of the present invention 1 is processed.For the effect of the inventive method is described better, Fig. 2 adopts existing method, the high dynamic range images that the high dynamic range image tone mapping method based on Retinex shows after processing, Fig. 3 is that comparison diagram is amplified in the part of Fig. 1 and Fig. 2, wherein the first half of Fig. 3 is the partial enlarged drawing at the black surround position in Fig. 1, and the Lower Half of Fig. 3 is the partial enlarged drawing at the black surround position in Fig. 2.From Fig. 3, can contrast and find out, adopt the inventive method to compare with the existing method based on Retinex, can remove better " halation " phenomenon existing after high dynamic range image tone mapping.What deserves to be explained is, the inventive method and existing method are colored images for what process, owing to declaring the requirement of text, limit, and institute's drawings attached has become gray-scale map and shown, its " halation " phenomenon does not have coloured image true to nature.

The tone mapping method of high dynamic range images of the present invention, for " halation " phenomenon easily producing in localization tone mapping method, estimates illumination component by WLS filtering, can avoid comparison of light and shade strongly to locate " halation " phenomenon producing; By removing the gray level at two extreme 1% places, prevent under-exposure and generation overexposure, adopt self-adaptation adjustment function to regulate the light and shade of image, make the image after tone mapping have the advantages that contrast is high, details display effect is good.

Claims (2)

1. a high dynamic range image tone mapping method, is characterized in that, according to following steps, implements:

Step 1, obtains the luminance picture L of high dynamic range images _in, and the formation log-domain luminance picture L that takes the logarithm, R wherein, G, B are respectively the red, green, blue color value of each pixel of high dynamic range images, and it is calculated as:

L _in＝0.299R+0.587G+0.114B，

L＝log(L _in+0.00001)；

Step 2, carries out multiple dimensioned WLS filtering to L, estimates multiple dimensioned illumination component L _k, k=1 wherein, 2 ..., to avoid comparison of light and shade strongly to locate " halation " phenomenon producing, it is expressed as:

L _k＝WLS(L,λ _k)，

Wherein operator WLS () represents to carry out WLS filtering, λ _krepresent scale factor, its value has determined illumination component image L _klevel and smooth degree, increase λ _k, will make level and smooth degree increase;

Step 3, adopts multiple dimensioned Retinex method to recover the brightness composition of high dynamic range images, that is:

Wherein N represents yardstick number, ω _kfor the weight coefficient of different scale, and

Step 4, to R _lfetching number, obtains R ₁, that is: R ₁=exp (R _l);

Step 5, cancellation R ₁two extreme 1% gray level, prevents under-exposure and generation overexposure, and is normalized, and obtains R ₂, that is:

Wherein, m _sr ₁after middle pixel value sorts from small to large, 1% the corresponding R in pixel place ₁value; m _lr ₁after middle pixel value sorts from small to large, 99% the corresponding R in pixel place ₁value;

Step 6, adopts self-adaptation adjustment function to R ₂regulate, and its gray-scale value is mapped to the scope of [0,255], that is: wherein, regulate parameter b can obtain the image of different bright-dark degrees, the span of b is [0.5,1.0];

Step 7, introduces index and controls saturation degree, adopts following computing formula, carries out color recovery:

complete high dynamic range image tone mapping,

Its Exponential s is for controlling saturation degree, R _out, G _out, B _outbe respectively the red, green, blue color value that high dynamic range images finally obtains after tone mapping.

2. a kind of high dynamic range image tone mapping method according to claim 1, is characterized in that: the multiple dimensioned WLS in described step 2 is filtered into: L _k=(I+ λ _kl _g) ^-1l,

Wherein, I is unit matrix, λ _kfor scale factor, L _gfor:

Wherein, D _x, D _ybe respectively horizontal and vertical direction differential sampling parameter, T represents transpose of a matrix, A _x, A _ybe diagonal matrix, its diagonal entry is respectively a _x,p(L), a _y,p(L), it is calculated as:

Wherein parameter alpha is used for controlling the sensitivity of smoothing process to image border, and span is 1.0-1.8; Parameter l=log (L+0.000001), constant ε is 0.00001.