CN102186020A - Image processing apparatus and image processing method - Google Patents
Image processing apparatus and image processing method Download PDFInfo
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Abstract
An image processing apparatus includes a selecting unit selecting a reference image from input images, a calculating unit calculating brightness ratios of the remaining input images as gains, a calculating unit calculating first weights for the remaining input images and calculating a second weight based on a brightness of image data as a synthesized image of the input image with the first weights, a generating unit generating a high-contrast image by performing weighting synthesis on the input images using the first weights and the second weight, a preparing unit preparing a tone conversion curve based on a brightness distribution of the high-contrast image and a brightness distribution as conversion target, and a generating unit performing the tone conversion on the high-contrast image based on the tone conversion curve, and generating the output image having the narrow tonal range.
Description
Technical field
The present invention relates to image processing apparatus and image processing method.
Background technology
Now, in order to obtain the contrast preferable image, the method that is adopted is to synthesize by many different input pictures of exposure to the shooting Same Scene, thereby generates the composograph that dynamic range is enlarged.And, proposed a kind of composograph (high-contrast image) and carried out greyscale transformation based on this gray scale amplitude broad, also generate the method (for example, patent documentation 1) of the output image of the narrow final result of gray scale amplitude thus.
According to this method,, therefore can obtain the contrast preferable image owing to generated the output image of the information (particularly half-tone information) of the high-contrast image that has kept the gray scale amplitude broad.
The prior art document
Patent documentation
Patent documentation 1: No. the 3956311st, Japan's special permission
The problem to be solved in the present invention
Above-mentioned existing method is carried out according to a kind of like this conversion characteristics, promptly based on the feature of the Luminance Distribution of high-contrast image (composograph), be specially, the characteristic point of minimum brightness, intermediate luminance, 3 points of maximum brightness, the greyscale transformation of calculating the output image that is used to generate final result.But, in this greyscale transformation, still can produce gray scale and jump, particularly can exist low-light level portion, the gray scale of high brightness portion shows factitious problem at image.So, just can not obtain the output image that the contrast preferable image is used as final result.
Summary of the invention
The present invention is used to solve above-mentioned prior art problems.The objective of the invention is to provide a kind of and can obtain image processing apparatus and the image processing method that the contrast preferable image is used as the output image of final result.
The means of dealing with problems
The 1st inventive images processing unit, composograph based on the gray scale amplitude broad that makes dynamic range expansion that many different input pictures of exposure of taking Same Scene are synthesized into is a high-contrast image, generate the gray scale amplitude output image narrower than above-mentioned high-contrast image, comprise: selected unit, based on the information of the brightness composition of above-mentioned many input picture, selected reference image among above-mentioned many input pictures; The gain calculating unit, information based on the brightness composition of above-mentioned many input pictures, for the remaining input picture of removing the said reference image in above-mentioned many, calculating with above-mentioned benchmark image is that benchmark and brighteness ratio above-mentioned remaining input picture are used as gain; Weight calculation unit, information based on the brightness composition of above-mentioned gain that calculates and said reference image, calculate the 1st weight that is applicable to above-mentioned remaining input picture, and, based on utilizing above-mentioned the 1st weight above-mentioned many input pictures to be weighted the result's of compose operation the information of brightness composition of view data, calculate the 2nd weight; The intermediate image generation unit, above-mentioned the 1st weight that utilization calculates and above-mentioned the 2nd weight are weighted synthetic to above-mentioned many input pictures, generate above-mentioned high-contrast image thus; Production unit based on the information of the shape of the Luminance Distribution of the information of the shape of the Luminance Distribution of the above-mentioned high-contrast image that is generated and predefined conversion target, is made the gray-scale transformation curve of the characteristic of expression greyscale transformation; And the output image generation unit, carry out the greyscale transformation of above-mentioned high-contrast image based on the above-mentioned gray-scale transformation curve of made, generate the output image narrower than the gray scale amplitude of this high-contrast image.
The 2nd invention is according to the 1st invention, above-mentioned selected unit is based on the information of the brightness composition of the downscaled images after above-mentioned many input pictures are dwindled respectively, a wideest input picture of effective breadth of selected Luminance Distribution from above-mentioned many is as the said reference image.
The 3rd invention is according to the 1st invention and the 2nd invention, above-mentioned gain calculating unit is based on the information of the brightness composition of the downscaled images after above-mentioned many input pictures are dwindled respectively, to above-mentioned remaining input picture, calculating with above-mentioned benchmark image is benchmark to be used as above-mentioned gain with brighteness ratio above-mentioned remaining input picture.
The 4th invention is any one in inventing according to the 1st to the 3rd, above-mentioned weight calculation unit, for the value of the above-mentioned gain that the calculates above-mentioned remaining input picture littler,, the weight of the hi-lite of this input picture calculates above-mentioned the 1st weight so that becoming big mode than setting; For the value of the above-mentioned gain that the calculates above-mentioned remaining input picture bigger,, the weight of the low-light level of this input picture part calculates above-mentioned the 1st weight so that becoming big mode than setting.
The 5th invention is any one in inventing according to the 1st to the 4th, above-mentioned weight calculation unit calculates following ratio as above-mentioned the 2nd weight, and above-mentioned ratio is for setting up the ratio of obtaining accordingly to the high-high brightness of view data of using above-mentioned the 1st weight above-mentioned many input pictures to be weighted the result of compose operation with the maximum on regulation " N " bit gradation that dynamic range has been enlarged.
The 6th invention is any one in inventing according to the 1st to the 5th, above-mentioned production unit, from the Luminance Distribution shape information of the shape information of the Luminance Distribution of the above-mentioned high-contrast image that generates and predefined conversion target, extract the information of corresponding relation of brightness value of the above-mentioned output image of the above-mentioned high-contrast image in expression conversion source and conversion destination, represent the gray-scale transformation curve of the characteristic of greyscale transformation based on this information issuing that extracts.
The 7th invention is any one in inventing according to the 1st to the 6th, above-mentioned production unit is based on only being the shape information of the Luminance Distribution of the shape information of the object Luminance Distribution of making and above-mentioned conversion target with following pixel, generate the gray-scale transformation curve of the characteristic of expression greyscale transformation, above-mentioned pixel is to belong to predetermined in the tonal range of above-mentioned high-contrast image or by the pixel of the tonal range of user's appointment.
The 8th invention is any one in inventing according to the 1st to the 7th, and the shape information of above-mentioned Luminance Distribution is the shape information of cumulative histogram.
The 9th invention is any one in inventing according to the 1st to the 8th, and the composograph of above-mentioned gray scale amplitude broad is that above-mentioned high-contrast image is to compare the many images of grey with above-mentioned many input pictures.
The 10th inventive images processing method, composograph based on the gray scale amplitude broad that makes dynamic range expansion that many different input pictures of exposure of taking Same Scene are synthesized into is a high-contrast image, generate the gray scale amplitude output image narrower than above-mentioned high-contrast image, comprise: selected step, based on the information of the brightness composition of above-mentioned many input picture, selected reference image among above-mentioned many input pictures; The gain calculating step, information based on the brightness composition of above-mentioned many input pictures, for the remaining input picture of removing the said reference image in above-mentioned many, calculating with above-mentioned benchmark image is that benchmark and brighteness ratio above-mentioned remaining input picture are used as gain; The weight calculation step, information based on the brightness composition of above-mentioned gain that calculates and said reference image, calculate the 1st weight that is applicable to above-mentioned remaining input picture, and, based on utilizing above-mentioned the 1st weight above-mentioned many input pictures to be weighted the result's of compose operation the information of brightness composition of view data, calculate the 2nd weight; Intermediate image generates step, and above-mentioned the 1st weight that utilization calculates and above-mentioned the 2nd weight are weighted synthetic to above-mentioned many input pictures, generate above-mentioned high-contrast image thus; Making step based on the information of the shape of the Luminance Distribution of the information of the shape of the Luminance Distribution of the above-mentioned high-contrast image that is generated and predefined conversion target, is made the gray-scale transformation curve of the characteristic of expression greyscale transformation; And output image generates step, carries out the greyscale transformation of above-mentioned high-contrast image based on the above-mentioned gray-scale transformation curve of made, generates the output image narrower than the gray scale amplitude of this high-contrast image.
The 11st invention is according to the 10th invention, above-mentioned selected step is based on the information of the brightness composition of the downscaled images after above-mentioned many input pictures are dwindled respectively, a wideest input picture of effective breadth of selected Luminance Distribution from above-mentioned many is as the said reference image.
The 12nd invention is according to the 10th or the 11st invention, above-mentioned gain calculating step is based on the information of the brightness composition of the downscaled images after above-mentioned many input pictures are dwindled respectively, to above-mentioned remaining input picture, calculating with above-mentioned benchmark image is benchmark to be used as above-mentioned gain with brighteness ratio above-mentioned remaining input picture.
The 13rd invention is any one in inventing according to the 10th to the 12nd, above-mentioned weight calculation step, for the value of the above-mentioned gain that the calculates above-mentioned remaining input picture littler,, the weight of the hi-lite of this input picture calculates above-mentioned the 1st weight so that becoming big mode than setting; For the value of the above-mentioned gain that the calculates above-mentioned remaining input picture bigger,, the weight of the low-light level of this input picture part calculates above-mentioned the 1st weight so that becoming big mode than setting.
The 14th invention is any one in inventing according to the 10th to the 13rd, above-mentioned weight calculation step calculates following ratio as above-mentioned the 2nd weight, and above-mentioned ratio is for setting up the ratio of obtaining accordingly to the high-high brightness of view data of using above-mentioned the 1st weight above-mentioned many input pictures to be weighted the result of compose operation with the maximum on regulation " N " bit gradation that dynamic range has been enlarged.
The 15th invention is any one in inventing according to the 10th to the 14th, above-mentioned making step, from the Luminance Distribution shape information of the shape information of the Luminance Distribution of the above-mentioned high-contrast image that generates and predefined conversion target, extract the information of corresponding relation of brightness value of the above-mentioned output image of the above-mentioned high-contrast image in expression conversion source and conversion destination, represent the gray-scale transformation curve of the characteristic of greyscale transformation based on this information issuing that extracts.
The 16th invention is any one in inventing according to the 10th to the 15th, above-mentioned making step is based on only being the shape information of the Luminance Distribution of the shape information of the object Luminance Distribution of making and above-mentioned conversion target with following pixel, generate the gray-scale transformation curve of the characteristic of expression greyscale transformation, above-mentioned pixel is to belong to predetermined in the tonal range of above-mentioned high-contrast image or by the pixel of the tonal range of user's appointment.
The 17th invention is any one in inventing according to the 10th to the 16th, and the shape information of above-mentioned Luminance Distribution is the shape information of cumulative histogram.
The 18th invention is any one in inventing according to the 10th to the 17th, and the composograph of above-mentioned gray scale amplitude broad is that above-mentioned high-contrast image is to compare the many images of grey with above-mentioned many input pictures.
The effect of invention
Adopt the present invention, can obtain the output image that the contrast preferable image is used as final result.
Description of drawings
Fig. 1 is the block diagram of formation that the image processing apparatus of execution mode is shown.
Fig. 2 is the flow chart (1/2) of operation that the image processing apparatus of execution mode is shown.
Fig. 3 is the flow chart (2/2) of operation that the image processing apparatus of execution mode is shown.
Fig. 4 is the figure of example that the brightness histogram of the brightness histogram of conversion target and its linear characteristic state is shown.
Fig. 5 is the figure of example that the cumulative histogram of the cumulative histogram of composograph and conversion target is shown.
Fig. 6 is the figure that the example of gray-scale transformation curve is shown.
The explanation of symbol
10 ... image processing apparatus (own), 11 ... control part, 12 ... the image unit accommodation section, 13 ... buffer memory, 14 ... data processing division, 15 ... compression/lsb decoder, 16 ... recording medium, 17 ... display, 18 ... operating portion, 19 ... system bus, 20 ... image unit
Embodiment
The various details execution mode.Fig. 1 is the block diagram of formation that the image processing apparatus of present embodiment is shown.As shown in Figure 1, the image processing apparatus of present embodiment comprises image processing apparatus 10 and connected image unit 20.
Image processing apparatus 10 has control part 11, image unit accommodation section 12, buffer memory 13, data processing division 14, compression/lsb decoder 15, recording medium 16, display 17, operating portion 18 and system bus 19.Here, control part 11, image unit accommodation section 12, buffer memory 13, data processing division 14, compression/lsb decoder 15, recording medium 16, display 17 connect by system bus 19.In addition, operating portion 18 is connected on the control part 11.
In addition, image unit 20 has: comprise the capture lens of a plurality of set of lenses formations of condenser lens, zoom lens, and make this capture lens move the lens drive division that focuses on adjustment, zoom adjustment along optical axis direction.And the focusing adjustment of capture lens, zoom adjustment basis are carried out from the indication of the control part 11 of image processing apparatus 10.
From the view data placeholder record of image unit 20 output buffer memory 13.In addition, view data of in the processing procedure of being undertaken, making etc. by control part 11 also placeholder record in this buffer memory 13.
Data processing division 14 to the view data of record in the buffer memory 13, is implemented the image processing of defect pixel revisal, light and shade (shading) revisal, white balance adjustment, interpolation, profile enhancing, gamma transformation etc. according to the indication of control part 11.And data processing division 14 is made of ASIC etc.
Compression/lsb decoder 15 compresses processing according to the indication of control part 11 to the view data of buffer memory 13.And compression is handled and is waited and carry out according to JPEG (Joint Photographic Experts Group) form.
And, in the image processing apparatus of present embodiment, many the different input pictures of exposure of taking Same Scene are synthesized, thereby generate the composograph that dynamic range is enlarged, carry out greyscale transformation based on this composograph (high-contrast image), finally, generate the narrow output image of gray scale amplitude.Thus, generated the good output image of contrast of the information (particularly half-tone information) of the high-contrast image that remains with the gray scale amplitude broad.
And, also enumerated an example of the gray scale of each image of handling about this image processing apparatus, for example, input picture is 256 (8 bits), 1024 (10 bit) gray scale, high-contrast image is 1024 (10 bits), 65536 (16 bit) gray scale, so output image is 1024 (10 bit) gray scale, more tractable 256 (8 bit) gray scale etc. usually.
Below, with reference to the flow chart description of Fig. 2 and Fig. 3 about the performed operation of the image processing apparatus of the present embodiment of this processing.
The processing of the flow chart of Fig. 2 and Fig. 3 is to obtain the processing of being called in (record) from image unit 20 outputs and by buffer memory 13 at many different images of the exposure of taking Same Scene.When calling this processing, many images in these buffer memorys 13 are designated as input picture (1～N).
And this many image can for example obtain by implementing to surround to expose to taking to wait.In this case, an image in these many be at AE (automatic exposure) definite or by the conditions of exposure of user's appointment under take, and, in addition residual image is to take down at the different conditions of exposure that is benchmark (conditions of exposure of benchmark ± n level) with this conditions of exposure, has so just implemented to surround exposure and has taken.
In addition, in the processing below,, just, carry out processing as input with the image of the linear characteristic state under the state of imaging apparatus output image signal composition not implement the image of gamma revisal (gamma transformation) etc.Therefore, be used as input picture (under 1～N) the situation at the image of having implemented gamma revisal image processing such as (gamma transformation), the picture signal composition is turned back to the linear characteristic state, in case original image is implemented contrary gamma revisal (contrary gamma transformation) afterwards, just used as input picture (1～N).
Step 101 (S101): (each of 1～N) is made downscaled images to 11 pairs of input pictures of control part.For example, on the direction in space of each input picture, the pixel value by obtaining 2 * 2 pixels or 4 * 4 pixels average etc. made downscaled images.And, the downscaled images that is generated (1～N) be recorded in the buffer memory 13 with input picture (in 1～N) the different zone.
Step 102: (each of 1～N) is made the histogram (brightness histogram) of brightness composition to the downscaled images of 11 pairs of mades of control part.
Step 103: the brightness histogram of 11 pairs of mades of control part is analyzed respectively, based on the result of this analysis, (selectes one 1～N) as benchmark image from input picture.
Concrete, at first, that obtains that the downscaled images that becomes the basis that brightness histogram makes becomes whole pixel counts for example becomes 0.1% pixel count (i).And this downscaled images is with respect to the ratio of whole pixel counts (0.1% etc.), with the pixel in the zone outside the pixel of the defect pixel of imaging apparatus or outstanding pixel value, noise etc., composing images, is appointed as not as the object that calculates.
Then, use the brightness histogram that generates, for example, if use the example of the brightness histogram of Fig. 4 here, so from the high brightness side (brightness value " 255 ") of its transverse axis (brightness) towards low-light level side (brightness value " 0 "), search the value and pixel count (i) consistent location of obtaining before of the longitudinal axis (pixel count) of brightness histogram, value (brightness value) conduct " max (brightness maximum) " of extracting the transverse axis of consistent location.In addition, then search for towards high brightness side (brightness value " 255 ") from the low-light level side (brightness value " 0 ") of the histogrammic transverse axis of same brightness (brightness), up to the value of the longitudinal axis that searches brightness histogram (pixel count) and pixel count (i) consistent location of obtaining before, extract value (brightness value) conduct " min (brightness minimum value) " of the transverse axis of consistent location.
Then, selected and the corresponding input picture of downscaled images (1) be as benchmark image, and this downscaled images is that make should " max (brightness maximum) " and the basis of the brightness histogram of the difference maximum of " min (brightness minimum value) ".
So, (the wideest image of the effective breadth of selected Luminance Distribution is as benchmark image 1～N) from input picture.
Step 104: control part 11 is benchmark based on the information of the brightness composition of downscaled images with the benchmark image, to each calculated gains of other input picture (removing the remaining input picture more than 1 outside the benchmark image).Concrete, according to following (formula 1) calculated gains (gain).Here, the f of (formula 1)
Y(x, y) the brightness composition of the downscaled images of expression benchmark image, h
Y(x y) represents the brightness composition of the downscaled images of other input picture of object as a comparison, in addition, and (x, y) coordinate position of each pixel in the expression downscaled images.But, carry out under the situation of the encompassed shooting of taking under the preassigned conditions of exposure, not needing calculated gains.
(formula 1)
And, under the situation of the yield value that calculates by (formula 1), be under conditions of exposure, to take with respect to the benchmark image under-exposure as " other input picture " of its calculating object less than 0.1 (gain＜0.1).In addition, under the situation of the yield value that calculates, be under the conditions of exposure over-exposed, to take with respect to benchmark image as " other input picture " of its calculating object greater than 0.1 (gain＞0.1).
Step 105: control part 11 is based on each gain that calculates and the information of the brightness composition of benchmark image, calculates the 1st weight for each of other input picture.Concrete, according to following (formula 2), calculate the weight (W) corresponding with yield value, and with it as the 1st weight.Here, the f of (formula 2)
Y(x, y) the brightness composition of expression benchmark image.In addition, " min " and " max " is when in the above-mentioned steps 103 during the selected reference image, " min (the brightness minimum value) " obtained from the brightness histogram corresponding with this benchmark image and " max (brightness maximum) ".According to this (formula 2),,, calculate the 1st weight based on the brightness of benchmark image for other input picture each.
(formula 2)
And, according to (formula 2), for " other input picture " under conditions of exposure, taken with respect to the benchmark image under-exposure, calculating according to (gain＜1.0 o'clock), make the weight of the hi-lite of image become big, the calculating of so carrying out the 1st weight is (still, at f
YDo not consider (formula 2) in the time of＜min and W is set at 0, at f
YDo not consider (formula 2) in the time of＞max and W is set at (2log
2(gain)).)。This is for for hi-lite, makes the information of " other input picture " taken than the benchmark image exposure more good with lacking.
In addition, for " other input picture " taken under the conditions of exposure over-exposed with respect to benchmark image, according to the calculating of (gain＞1.0 o'clock), make the weight of the low-light level part of image become big, the calculating of so carrying out the 1st weight is (still, at f
YDo not consider (formula 2) in the time of＜min and W is set at (2log
2(gain)), at f
YDo not consider (formula 2) in the time of＞max and W is set at 0.)。This is for for the low-light level part, makes the information of " other input picture " taken than the benchmark image exposure more good with Duoing.
Step 106: control part 11 uses the 1st weight that calculates, and according to following (formula 3), presses the shades of colour composition of R (r), G (g), B (b), and input picture (benchmark image and other input picture) is carried out the weighting compose operation.
(formula 3)
g
c(x，y)＝{f
c(x，y)+W
1h
1c(x，y)～W
n-1h
n-1c(x，y)}
…(3)
/(1.0+W
1～W
n-1)
c＝{r，g，b}
And, the f of (formula 3)
c(x, y) expression " benchmark image ", h
1c(x, y)～h
N-1c(x y) represents other input picture (1～N-1 just, removes the remaining input picture more than 1 of benchmark image).In addition, W
1～W
N-1Expression is for each other input picture (1～N-1) the 1st weight that calculates in above-mentioned steps 105, " 1.0 " expression is at the weight of benchmark image, the number (N) of " n " expression input picture, the shades of colour composition of " c " expression R (r), G (g), B (b).Then, g
c(x y) is each result of calculation by weighting compose operation gained to the shades of colour composition of R (r), G (g), B (b), just, is the view data after synthetic.
Concrete, according to following (formula 4), at first, based on operation result g
r(x, y), g
g(x, y), g
b(x, view data y) are calculated brightness data g
Y(x, y).Then, the brightness data g from calculating
Y(x, y) in, use function " Max () " to extract the maximum of brightness.Then, the maximum on the brightness maximum that calculating is extracted and " N " bit gradation of regulation, for example, the ratio under the situation of " N=16 " bit between its maximum " 65535 " is used as the 2nd weight " NbitW ".
(formula 4)
g
Y(x，y)＝0.299g
r(x，y)+0.587g
g(x，y)+0.114g
b(x，y)
Step 107: control part 11 uses the 1st weight and this two classes weight of the 2nd weight that calculates, adopt following (formula 5) synthetic, be produced on the composograph (high-contrast image) that on the gray scale amplitude shown in " N " bit gradation of afore mentioned rules dynamic range is enlarged with the weighting that every kind of color component of R (r), G (g), B (b) carries out input picture (benchmark image and other input picture).
(formula 5)
g
c(x，y)＝{NbitW(f
c(x，y)+W
1h
1c(x，y)～W
n-1h
n-1c(x，y))}
…(5)
/(1.0+W
1～W
n-1)
c＝{r，g，b}
And, the g of (formula 5)
c(x, the y) high-contrast image of expression making, f
c(x, y) expression " benchmark image ", h
1c(x, y)～h
N-1c(x y) represents other input picture (1～N-1 just, removes the remaining input picture more than 1 of benchmark image).In addition, W
1～W
N-1Expression is with respect to each other input picture (1～N-1) the 1st weight that calculates in above-mentioned steps 105, " 1.0 " expression is with respect to the weight of benchmark image, the number (N) of " n " expression input picture, the shades of colour composition of " c " expression R (r), G (g), B (b), " NbitW " is illustrated in the 2nd weight that calculates in the above-mentioned steps 106.
Like this, in the image processing apparatus of present embodiment, only just calculate weight (above-mentioned steps 105,106), and it is applicable to R (r), the G (g) of input picture, whole shades of colour compositions of B (b) based on the brightness composition, thereby in order to carry out synthetic handle (this step 107) of weighting.Therefore, in the high-contrast image that is generated, under the state of so keeping, positively reflected the colour balance of each input picture.
In addition, with above-mentioned different, if it is (concrete to have generated high-contrast image according to each color component of R (r), the G (g) of input picture, B (b), the part of handling under above-mentioned brightness composition (except the 2nd weight calculation processing of step 106) is all replaced with the processing of each color component), just can demonstrate the gray scale amplitude more effectively.
Step 108: control part 11 calls the subprogram of greyscale transform process shown in Figure 3.
(Fig. 3: greyscale transform process)
Step 108-1 (S108-1): control part 11 is at first determined in the greyscale transformation Luminance Distribution as the conversion target, make the brightness histogram of expression as the Luminance Distribution of this conversion target, and the brightness histogram of the Luminance Distribution of expression composograph (high-contrast image).
Here, though be the brightness histogram of conversion target, but suppose that visually the brightness histogram of preferred image is more at the pixel count of intermediate light part, as the conversion target, determine for example the sort of Luminance Distribution of the brightness histogram that is the Gaussian Profile shape shown in Fig. 4 (a), based on this Luminance Distribution, make making the picture signal composition be the brightness histogram of the state of linear characteristic.For example, be at the picture signal composition shown in Fig. 4 (a) under the situation of state of linear characteristic, generate the brightness histogram of the Luminance Distribution shown in Fig. 4 (b).Then, the brightness histogram of the state of this linear characteristic of generation also will be used as the conversion target.
And, the composograph (high-contrast image) that dynamic range is enlarged is to synthesize made by the weighting of above-mentioned steps 107, be not limited to make the information of this " N " bit gradation all effective, also be not limited to show the gray scale in the zone of being paid close attention on the image.
Therefore, the scope of exporting as the output image of the final result in the tonal range of composograph (high-contrast image) (tonal range) for example also can be specified by the user.Then, for example, based on the minimum value " outputMin " of the tonal range of user's appointment and the information of maximum " outputMax ", in the pixel of composograph (high-contrast image), for having the pixel that is not included in the pixel value within the scope of being somebody's turn to do " outputMin " and " outputMax " expression, just from the object that the brightness histogram of above-mentioned composograph (high-contrast image) is made, remove.
Like this, wait the gray scale part of at random specifying and exporting the zone of being paid close attention to that is considered to effective gray scale part of composograph (high-contrast image) or image as the output image of final result by the user.In addition, minimum value of tonal range " outputMin " and maximum " outputMax " are not the values of user's appointment, certainly, can use the preset value that preestablishes device yet.
So make after the brightness histogram, control part 11 is made cumulative histogram respectively to the brightness histogram of this composograph and the brightness histogram of conversion target.
And, according to the cumulative histogram of conversion target, generate the pairing content of gray scale amplitude of the output image of the final result narrower than composograph (high-contrast image) gray scale amplitude.Also can, generate the brightness histogram of the pairing content of gray scale amplitude of output image, and generate cumulative histogram based on this.
Step 108-2: control part 11 is made the greyscale transformation table based on the cumulative histogram of making.
Concrete, at first, with the longitudinal axis (pixel count is shown) of the cumulative histogram of the cumulative histogram of composograph and conversion target " n " five equilibrium respectively.And, at this moment, be that the existing scope of the data on the longitudinal axis is carried out " n " five equilibrium.
Here, show the longitudinal axis by the example of the situation of " n=16 " five equilibrium.
Fig. 5 (a) is under 1200 * 1600 pixel resolutions, according to the example of the cumulative histogram of composograph (high-contrast image) made that has enlarged dynamic range with 16 bit gradation.The existing scope of the data of the longitudinal axis according to boundary line " a0～a16 " by 16 five equilibriums.And under the situation of this example, the maximum of the longitudinal axis is 1920000 (1200 * 1600 pixels), and the maximum of transverse axis is 65535 (16 bit gradation).
In addition, Fig. 5 (b) is corresponding to the example as the cumulative histogram of the conversion target of gray scale amplitude (this situation the is 10 bit gradation) made of the output image of final result made.The existing scope of the data of the longitudinal axis according to boundary line " b0～b16 " by 16 five equilibriums.And, under the situation of this example, the maximum of the longitudinal axis is 1023 (10 bit gradation), and therefore the maximum of the longitudinal axis is 1920000 (1200 * 1600 pixels) owing to come normalization according to the cumulative histogram of the composograph (high-contrast image) of Fig. 5 (a) in addition.
The longitudinal axis of cumulative histogram is by after " n " five equilibrium, and then, the represented brightness value of each boundary line in the zone of this five equilibrium and the intersection point of the curve of cumulative data is set up corresponding between the cumulative histogram of composograph and conversion target.In the example of Fig. 5, " a0Y～a16Y " of Fig. 5 of the cumulative histogram of composograph (a), corresponding respectively with Fig. 5 (b) of the cumulative histogram of conversion target " b0Y～b16Y ".
Then, be produced on the information of the corresponding relation of these brightness values of expression between the cumulative histogram of the cumulative histogram of composograph and conversion target as the greyscale transformation table.
So, control part 11 generates the greyscale transformation table based on the cumulative histogram of composograph and conversion target.
Step 108-3: control part 11 generates gray-scale transformation curve based on the greyscale transformation table of made.For example, making gray-scale transformation curve as shown in Figure 6.Concrete, with reference to the greyscale transformation table, take out the brightness value of the cumulative histogram of composograph (high-contrast image) from the transverse axis of Fig. 6, " a0Y "～" a16Y " on Fig. 5 (a) for example, and take out the brightness value of the cumulative histogram of conversion target, for example " b0Y "～" b16Y " on Fig. 5 (b) from the longitudinal axis of Fig. 6.Then, with each intersection point between these " a0Y "～" a16Y " and " b0Y "～" b16Y " is datum mark, do not producing on each datum mark between these each datum marks jumpy, implementing processing such as linear interpolation, smoothing, generating gray-scale transformation curve as shown in Figure 6.
In the making of this gray-scale transformation curve is handled, if do not make the curve that inclination between the datum mark has surpassed the ratio between the gray scale amplitude of the gray scale amplitude of composograph (high-contrast image) and output image, just in the example of Fig. 6, if there is not to generate the curve of 64 times of the ratios exceed between 16 bit gradation and 10 bit gradation, the jump of gray scale just can not appear in the greyscale transform process below this use gray-scale transformation curve so.
Further, though from foregoing description, can recognize, but the example of the gray-scale transformation curve of Fig. 6 is that the composograph (high-contrast image) that makes 16 bit gradation that dynamic range enlarges is carried out greyscale transformation, also can be used to generate the output image of 10 narrow bit gradation of gray scale amplitude.
Step 108-4: control part 11 is carried out the greyscale transformation of composograph based on the gray-scale transformation curve of making, and the image after this processing is stored in the buffer memory 13.Thus, from buffer memory 13, obtain the narrow output image of gray scale amplitude than composograph (high-contrast image).The output image that so obtains becomes the contrast preferable image of the information (particularly half-tone information) of the high-contrast image that has kept broad gray scale amplitude.
When control part 11 finishes in above-mentioned greyscale transform process, turn back to the processing of the flow chart of Fig. 2, transfer to step 109 (S109).
Step 109 (Fig. 2): control part 11 driving data handling parts 14, in buffer memory 13, the image after the greyscale transformation of obtaining implemented necessary image processing such as gamma transformation.
Step 110: control part 11 drive compression/lsb decoder 15, the image after the image processing of buffer memory 13 is implemented compression handle, and the image after this compression of recording medium 16 storages is handled.Then, the processing of control part 11 process ends.
And, on above-mentioned step 109, can also be in the content of the image after display image on the display 17 is handled.
(action effect of execution mode)
In the image processing apparatus of present embodiment, (1～N) makes downscaled images to each input picture, and based on the analysis result of the brightness histogram of each downscaled images, the wideest image of the effective breadth of selected Luminance Distribution is as benchmark image from input picture.And for example the pixel value by obtaining n * n (n 〉=2) pixel of each input picture on direction in space is average, makes downscaled images.
Next, information based on the brightness composition of downscaled images, for each other input picture, with the benchmark image is that benchmark calculates and the brighteness ratio of other input picture (removing the remaining input picture more than 1 outside the benchmark image) is used as gain, information based on the brightness composition of this each gain that calculates and benchmark image calculates the 1st weight that is applicable to each other input picture.
In addition, use the 1st weight that calculates, carry out the weighting compose operation of input picture (benchmark image and other input picture),, calculate the 2nd weight based on the view data of this operation result.
Then, use the 1st weight and the 2nd weight, the weighting of carrying out input picture is synthetic, is produced on the composograph (high-contrast image) that on the shown gray scale amplitude of " N " bit gradation of regulation dynamic range is enlarged.
Thus, in the image processing apparatus of present embodiment, (information of 1～N) " downscaled images " is carried out selected reference image, calculated gains, also has the calculating of the 1st weight based on having dwindled input picture.
Therefore, in becoming the input picture of synthetic object, comprised when producing the pixel of noise, in high-contrast image, also reduced this noise contribution by the synthetic made of weighting.In addition, when in input picture, having comprised pixel with outstanding pixel value, in high-contrast image by the synthetic made of weighting, the jump that also is not easy to produce gray scale.
In addition, the peaked ratio in the high-high brightness of the view data of the weighting compose operation result by obtaining input picture and regulation " N " bit gradation that dynamic range is enlarged is carried out the calculating of the 2nd weight.
Therefore, composograph (high-contrast image) by the synthetic input picture made of weighting, though its gray scale amplitude enlarges the gray scale amplitude that illustrates on the regulation wideer than input picture " N " bit gradation, but in high-contrast image, gray scale shows become nature and the jump that is not easy to produce gray scale.
In addition, in the image processing apparatus of present embodiment, other input picture of the gain that calculates (based on the brighteness ratio of benchmark image) value less (gain＜1.0), just, to other input picture of under conditions of exposure, taking, so that the weight of the hi-lite of image becomes the calculating that big mode is carried out the 1st weight with respect to the benchmark image under-exposure.Like this, compared with benchmark image, other input picture that the mode that tails off with exposure is taken under the situation of under-exposure can make the information of its hi-lite good.
In addition, the yield value that calculates is other input picture of big (gain＞1.0), just, to other input picture of under the conditions of exposure over-exposed, taking, so that the weight of the low-light level of image part becomes the calculating that big mode is carried out the 1st weight with respect to benchmark image.Like this, compared with benchmark image,, can make the information of its low-light level part good with other input picture that the big mode of exposure quantitative change is taken under over-exposed situation.
Therefore, when in becoming the input picture of synthetic object, having comprised the part that makes brightness change level and smooth structure, in high-contrast image by the synthetic made of weighting, the jump that also is not easy to produce gray scale.
In addition, in the image processing apparatus of present embodiment, (in 1～N), the wideest image of the effective breadth of selected Luminance Distribution is carried out the calculating of gain calculating and the 1st weight as benchmark image based on this benchmark image at input picture.Then, use this weight, the weighting of carrying out benchmark image and other input picture is synthetic, generates high-contrast image.
Thus, in the image processing apparatus of present embodiment, owing to come carries out image synthetic as the basis with the wideest benchmark image of the effective breadth of Luminance Distribution, therefore compared with prior art, by synthetic, can reduce the noise and the gray scale that in high-contrast image, produce and jump.
In addition, in the image processing apparatus of present embodiment, for the brightness histogram of expression, generate cumulative histogram respectively as the Luminance Distribution of the brightness histogram of the Luminance Distribution of conversion target and expression composograph.Cumulative histogram for the conversion target, compared with the composograph (high-contrast image) that on the shown gray scale amplitude of regulation " N " bit gradation, dynamic range is enlarged, make the gray scale amplitude institute content corresponding of the output image of the narrow final result of gray scale amplitude.
Next, based on the cumulative histogram of the composograph of making and the cumulative histogram of conversion target, generate the greyscale transformation table.At length, the longitudinal axis (pixel count) to the cumulative histogram of the cumulative histogram of the composograph made and conversion target carries out " n " five equilibrium respectively, " n=16 " five equilibrium for example, the shown brightness value of the intersection point of the boundary line of this five equilibrium gained and the curve of cumulative data is set up corresponding between two cumulative histograms.Therefore, the information issuing with this corresponding relation of expression is the greyscale transformation table.
In addition, make gray-scale transformation curve based on the greyscale transformation table of making.At length, with reference to the greyscale transformation table, brightness value on the cumulative histogram that extracts composograph on the transverse axis, and the brightness value on the cumulative histogram that extracts the conversion target on the longitudinal axis, obtain their intersection point (datum mark), between each datum mark of being obtained, implement processing such as linear interpolation, smoothing.Then, be made as gray-scale transformation curve by these curves of handling the result of gained.
After this, carry out the greyscale transformation of composograph based on the gray-scale transformation curve of made.By this greyscale transformation, generate the output image of the final result narrower than composograph (high-contrast image) gray scale amplitude.The image that so obtains (output image) becomes the contrast preferable image of the information (particularly half-tone information) of the high-contrast image that maintains broad gray scale amplitude.
So,, can obtain the output image that the contrast preferable image is used as final result by the image processing apparatus of present embodiment.
(other)
In the present invention, surround the exposure shooting and also can be applicable to miscellaneous equipment, for example, digital camera (digital still camera), Digital Video, mobile phone etc.And the present invention also is applicable to can be by the microscope that uses image that capturing element obtained shot object image is observed etc.
Claims (18)
1. image processing apparatus, composograph based on the gray scale amplitude broad that makes dynamic range expansion that many different input pictures of exposure of taking Same Scene are synthesized into is a high-contrast image, generate the gray scale amplitude output image narrower than above-mentioned high-contrast image, it is characterized in that, comprising:
Selected unit, based on the information of the brightness composition of above-mentioned many input picture, selected reference image among above-mentioned many input pictures;
The gain calculating unit, information based on the brightness composition of above-mentioned many input pictures, for the remaining input picture of removing the said reference image in above-mentioned many, calculating with above-mentioned benchmark image is that benchmark and brighteness ratio above-mentioned remaining input picture are used as gain;
Weight calculation unit, information based on the brightness composition of above-mentioned gain that calculates and said reference image, calculate the 1st weight that is applicable to above-mentioned remaining input picture, and, based on utilizing above-mentioned the 1st weight above-mentioned many input pictures to be weighted the result's of compose operation the information of brightness composition of view data, calculate the 2nd weight;
The intermediate image generation unit, above-mentioned the 1st weight that utilization calculates and above-mentioned the 2nd weight are weighted synthetic to above-mentioned many input pictures, generate above-mentioned high-contrast image thus;
Production unit based on the information of the shape of the Luminance Distribution of the information of the shape of the Luminance Distribution of the above-mentioned high-contrast image that is generated and predefined conversion target, is made the gray-scale transformation curve of the characteristic of expression greyscale transformation; And
The output image generation unit is carried out the greyscale transformation of above-mentioned high-contrast image based on the above-mentioned gray-scale transformation curve of made, generates the output image narrower than the gray scale amplitude of this high-contrast image.
2. the image processing apparatus of putting down in writing as claim 1, it is characterized in that, above-mentioned selected unit is based on the information of the brightness composition of the downscaled images after above-mentioned many input pictures are dwindled respectively, a wideest input picture of effective breadth of selected Luminance Distribution from above-mentioned many is as the said reference image.
3. the image processing apparatus of putting down in writing as claim 1, it is characterized in that, above-mentioned gain calculating unit is based on the information of the brightness composition of the downscaled images after above-mentioned many input pictures are dwindled respectively, to above-mentioned remaining input picture, calculating with above-mentioned benchmark image is benchmark to be used as above-mentioned gain with brighteness ratio above-mentioned remaining input picture.
4. the image processing apparatus of putting down in writing as claim 1, it is characterized in that, above-mentioned weight calculation unit for the value of the above-mentioned gain that the calculates above-mentioned remaining input picture littler than setting, is calculated above-mentioned the 1st weight so that the weight of the hi-lite of this input picture becomes big mode; For the value of the above-mentioned gain that the calculates above-mentioned remaining input picture bigger,, the weight of the low-light level of this input picture part calculates above-mentioned the 1st weight so that becoming big mode than setting.
5. the image processing apparatus of putting down in writing as claim 1, it is characterized in that, above-mentioned weight calculation unit calculates following ratio as above-mentioned the 2nd weight, and above-mentioned ratio is for setting up the ratio of obtaining accordingly to the high-high brightness of view data of using above-mentioned the 1st weight above-mentioned many input pictures to be weighted the result of compose operation with the maximum on regulation " N " bit gradation that dynamic range has been enlarged.
6. the image processing apparatus of putting down in writing as claim 1, it is characterized in that, above-mentioned production unit, from the Luminance Distribution shape information of the shape information of the Luminance Distribution of the above-mentioned high-contrast image that generates and predefined conversion target, extract the information of corresponding relation of brightness value of the above-mentioned output image of the above-mentioned high-contrast image in expression conversion source and conversion destination, represent the gray-scale transformation curve of the characteristic of greyscale transformation based on this information issuing that extracts.
7. the image processing apparatus of putting down in writing as claim 1, it is characterized in that, above-mentioned production unit is based on only being the shape information of the Luminance Distribution of the shape information of the object Luminance Distribution of making and above-mentioned conversion target with following pixel, generate the gray-scale transformation curve of the characteristic of expression greyscale transformation, above-mentioned pixel is to belong to predetermined in the tonal range of above-mentioned high-contrast image or by the pixel of the tonal range of user's appointment.
8. the image processing apparatus of putting down in writing as claim 1 is characterized in that, the shape information of above-mentioned Luminance Distribution is the shape information of cumulative histogram.
9. the image processing apparatus of putting down in writing as claim 1 is characterized in that, the composograph of above-mentioned gray scale amplitude broad is that above-mentioned high-contrast image is to compare the many images of grey with above-mentioned many input pictures.
10. image processing method, composograph based on the gray scale amplitude broad that makes dynamic range expansion that many different input pictures of exposure of taking Same Scene are synthesized into is a high-contrast image, generate the gray scale amplitude output image narrower than above-mentioned high-contrast image, it is characterized in that, comprising:
Selected step, based on the information of the brightness composition of above-mentioned many input picture, selected reference image among above-mentioned many input pictures;
The gain calculating step, information based on the brightness composition of above-mentioned many input pictures, for the remaining input picture of removing the said reference image in above-mentioned many, calculating with above-mentioned benchmark image is that benchmark and brighteness ratio above-mentioned remaining input picture are used as gain;
The weight calculation step, information based on the brightness composition of above-mentioned gain that calculates and said reference image, calculate the 1st weight that is applicable to above-mentioned remaining input picture, and, based on utilizing above-mentioned the 1st weight above-mentioned many input pictures to be weighted the result's of compose operation the information of brightness composition of view data, calculate the 2nd weight;
Intermediate image generates step, and above-mentioned the 1st weight that utilization calculates and above-mentioned the 2nd weight are weighted synthetic to above-mentioned many input pictures, generate above-mentioned high-contrast image thus;
Making step based on the information of the shape of the Luminance Distribution of the information of the shape of the Luminance Distribution of the above-mentioned high-contrast image that is generated and predefined conversion target, is made the gray-scale transformation curve of the characteristic of expression greyscale transformation; And
Output image generates step, carries out the greyscale transformation of above-mentioned high-contrast image based on the above-mentioned gray-scale transformation curve of made, generates the output image narrower than the gray scale amplitude of this high-contrast image.
11. image processing method as claim 10 record, it is characterized in that, above-mentioned selected step is based on the information of the brightness composition of the downscaled images after above-mentioned many input pictures are dwindled respectively, a wideest input picture of effective breadth of selected Luminance Distribution from above-mentioned many is as the said reference image.
12. image processing method as claim 10 record, it is characterized in that, above-mentioned gain calculating step is based on the information of the brightness composition of the downscaled images after above-mentioned many input pictures are dwindled respectively, to above-mentioned remaining input picture, calculating with above-mentioned benchmark image is benchmark to be used as above-mentioned gain with brighteness ratio above-mentioned remaining input picture.
13. image processing method as claim 10 record, it is characterized in that, above-mentioned weight calculation step for the value of the above-mentioned gain that the calculates above-mentioned remaining input picture littler than setting, is calculated above-mentioned the 1st weight so that the weight of the hi-lite of this input picture becomes big mode; For the value of the above-mentioned gain that the calculates above-mentioned remaining input picture bigger,, the weight of the low-light level of this input picture part calculates above-mentioned the 1st weight so that becoming big mode than setting.
14. image processing method as claim 10 record, it is characterized in that, above-mentioned weight calculation step calculates following ratio as above-mentioned the 2nd weight, and above-mentioned ratio is for setting up the ratio of obtaining accordingly to the high-high brightness of view data of using above-mentioned the 1st weight above-mentioned many input pictures to be weighted the result of compose operation with the maximum on regulation " N " bit gradation that dynamic range has been enlarged.
15. image processing method as claim 10 record, it is characterized in that, above-mentioned making step, from the Luminance Distribution shape information of the shape information of the Luminance Distribution of the above-mentioned high-contrast image that generates and predefined conversion target, extract the information of corresponding relation of brightness value of the above-mentioned output image of the above-mentioned high-contrast image in expression conversion source and conversion destination, represent the gray-scale transformation curve of the characteristic of greyscale transformation based on this information issuing that extracts.
16. image processing method as claim 10 record, it is characterized in that, above-mentioned making step is based on only being the shape information of the Luminance Distribution of the shape information of the object Luminance Distribution of making and above-mentioned conversion target with following pixel, generate the gray-scale transformation curve of the characteristic of expression greyscale transformation, above-mentioned pixel is to belong to predetermined in the tonal range of above-mentioned high-contrast image or by the pixel of the tonal range of user's appointment.
17. the image processing method as claim 10 record is characterized in that the shape information of above-mentioned Luminance Distribution is the shape information of cumulative histogram.
18. the image processing method as claim 10 record is characterized in that, the composograph of above-mentioned gray scale amplitude broad is that above-mentioned high-contrast image is to compare the many images of grey with above-mentioned many input pictures.
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