Method for correcting residual optical defects

Abstract

Method for correcting residual optical defects. One aspect of the invention relates to a method (400) for correcting residual optical defects in an image acquired by a camera with a given focal length, the acquired image being corrected for defects in a camera detector, the residual optical defects being relative to the given focal length and different from the detector defects, the method being carried out from a first calibration table corresponding to an amplitude of the residual optical defects at the given focal length. Figure to be published with the abbreviation: Figure 7

Description

Title of the invention: Method for correcting residual optical defects TECHNICAL FIELD OF THE INVENTION

[0001] The technical field of the invention is that of the correction of optical defects of an image acquired by an IR camera having a cooled detector.

[0002] The present invention relates to a method for correcting residual optical defects in an image acquired by a cooled and previously calibrated IR camera. TECHNOLOGICAL BACKGROUND OF THE INVENTION

[0003] In an infrared camera, each optical element generates a parasitic and spatially homogeneous thermal flux. In theory, the parasitic flux emitted by the camera's cryogenic detector may be imaged very diffusely by the detector or not at all.

[0004] Thus, the parasitic heat flux of the camera can be modeled as a spatially homogeneous background noise directly related to the ambient temperature of the camera's optical elements, excluding the detector. This phenomenon is due to radiative heat transfer between the internal optical elements of the camera and its detector. Figure 1 shows a graph of the temperature T of the parasitic heat flux received by the detector on the detector's center line (and therefore on the center line of the image it produces), with the abscissas corresponding to the pixels Pi_c of the center line. The graph is constant due to the homogeneity of the background noise and is equal to a constant temperature Te.

[0005] However, in some cases, the optical configuration of the infrared camera causes reflections of the heat flux emitted by the camera's cryogenic detector, which receives and images its own cold heat flux. Since a heat flux is greater when the temperature of a heat source to be imaged by the camera is higher, the cold flux from the cryogenic detector acts as a jump in the heat flux received by the camera, the detector's flux being colder than the thermal camera's flux.

[0006] Consequently, the heat transfer emitted by a source to be imaged is altered, and the flux received by the detector is composed of two fluxes: the thermal flux from the camera and the cold flux from the detector. The cold flux from the detector thus replaces the homogeneous parasitic hot flux coming from inside the camera.

[0007] This results in a temperature gradient on the detector, which translates into a gradient in "gray levels" and therefore a non-uniformity of noise in the image. The shape of the non-uniformity depends on the shape of the detector and the optical configuration of the camera. The intensity of the non-uniformity depends on the different temperatures Temperatures within the camera, for example, the detector temperature and the ambient temperature, as well as the integration time, are affected. Figure 2 is a graph representing the temperature of the flux received by the detector at the pixels Pi_c of the detector's centerline. Specifically, Figure 2 represents the temperature T of the flux received by the detector's centerline, part of which has a temperature corresponding to the temperature Te of the flux received by the camera, and part of which has a parasitic temperature Tp that depends on the temperature Td of the flux emitted by the detector and the temperature Te. In particular, the temperature Tp can be equal to: Tp — (1 - Σ2)*Tc + Σ2*Td, where G corresponds to the proportion of the camera's parasitic flux replaced by the detector's parasitic flux. The higher the detector's reflection, the higher H is.

[0008] When using a cooled infrared camera, it is possible to correct the non-uniform detector noise mentioned above by a one-point calibration process for example.

[0009] The one-point calibration of a cooled infrared camera consists of an adjustment of a gain table G and a shift table O (from the English "offset"), the adjustment being made from a defocused image or from a diaphragm (from the English "shutter") used to obtain an image assumed to be uniform on the sensor.

[0010] In particular, the response of a pixel to a light flux can be modeled by a linear function characterized by a slope representing a gain and a y-intercept representing a shift (commonly called an offset). Each pixel has its own gain and offset. Consequently, upon receiving a uniform light flux, the gray levels generated by the pixels differ, resulting in non-uniformities in the image generated by the camera.

[0011] Figure 3 shows an example of the response of a PI pixel and the response of a pixel P2, distinct from PI, is the response of a pixel corresponding to gray level values ​​N as a function of luminance L, which depends on the temperature T of the received flux. Thus, in [Fig. 3], each pixel response has a different slope—and therefore a different gain—and a different y-intercept—and therefore a different offset.

[0012] In order to eliminate pixel non-uniformities, it is necessary that the pixels have the same gain and the same offset. A correction is performed by applying the one-point calibration method, using a gain table G and an offset table O, each of which has the same dimensions as the detector matrix.

[0013] The gain table G is expressed as a table of coefficients, each coefficient being multiplied by a pixel in the same position. The gain table G is determined at the factory before the camera is put into service, for example. After its application, all pixels have the same response to a given flux variation, and their characteristic functions therefore have the same slope. The gain table can It can be determined by performing the first-order partial derivative of two images taken at two different scene temperatures. In particular, the partial derivative is performed with respect to the luminance parameter, which depends on the temperature.

[0014] The O offset table is additive with respect to the flux received by each of the pixels, and is therefore expressed in the form of a table of factors applied to each of the pixels, determined during the operation of the camera.

[0015] A shift table O is obtained from the image of a scene acquired in front of a diaphragm and denoted diaphragm, multiplied by the gain table G. In particular, the shift table O is obtained from the following formula:

[0016] O — Diaphragm*G - NloyemiU.ldiaphragnKA Each pixel of Average(ldiapiua£;me*G) comprises the average of all the pixels of the matrix Idiaptaagme*Cj . After its application, all pixels will have the same response to a given flux in the configuration where the calibration was performed.

[0017] Figure 4 is a block diagram of a one-point calibration method 100, based on a gain table G determined according to the method described above. Method 100 includes a camera shuttering step 101. In particular, the optical defects seen and corrected by the camera are not the same depending on the shuttering method chosen, as the shuttering can be achieved by defocusing, or by placing the camera diaphragm in front of the entire optical path or in front of the sensor.

[0018] The method further comprises a step 102 of calculating and applying an integration time. The method then comprises a step 103 of acquiring an image of the diaphragm Idiaphragm and then a step 104 of constructing the offset table O determined according to the preceding formula. Steps 101 to 104 correspond to the camera calibration phase.

[0019] In addition, the method 100 includes a step 105 of acquiring an arbitrary image Im by an operator with the integration time, then a step 106 of multiplying the acquired image by the gain table G and finally a step 107 of subtraction from the shift table O, which theoretically allows obtaining a final image Imf free from intrinsic detector defects and parasitic fluxes due to the camera.

[0020] In particular, if step 101 of the calibration method is performed with a diaphragm in front of a specific optical field, all optical reflection defects will be perfectly corrected. However, if there is a change in the camera's field of view, the O offset table is no longer valid; that is, it no longer corrects optical reflection defects because optical defects vary with the field. In the case of known cameras, calibration using the O offset table is performed in a specific optical configuration called the calibration field during The image stream from the scene is averaged across the sensor. Thus, the O offset table corrects defects seen only in this specific optical configuration. Non-uniformity defects or offsets (differences between the y-intercepts of pixel responses) in typical fields are not corrected because it is currently not known how to calculate a real-time offset table for typical fields, as this risks overwriting the visible scene within the offset table. In particular, if a defect appears locally in a field where the O offset table has not been generated, it is not corrected. This phenomenon is even more noticeable if the camera has continuous zoom and can image multiple fields.

[0021] If step 101 of the calibration method is performed by "defocusing," that is, if the optics are moved to defocus the image to the extreme (calibration field), any optical reflection defects—if any—are no longer present. Thus, when the O offset table is generated in this case, "optical reflection" defects are not taken into account, and only the intrinsic defects of the detector are corrected. When the camera "refocuses" the image, the image is calibrated, but the reflection defects are still visible because they were not present, i.e., not visible, when the O offset table was generated.

[0022] As a result, residual non-uniformities or optical defects, caused by parasitic flows internal to the camera, may remain present on the image despite a one-point calibration such as described above.

[0023] There is therefore a need to correct residual optical defects of an acquired and calibrated image. Summary of the invention

[0024] The invention provides a solution to the problems mentioned above by enabling the determination of residual optical defects in an image acquired at a given focal length and calibrated. The residual optical defects of the image are determined from at least one calibration table comprising values ​​of the residual defect amplitudes for the given focal length and an adaptation factor that takes into account the differences in acquisition conditions between the calibration table and the acquired image in order to correct the residual optical defects.

[0025] One aspect of the invention relates to a computer-implemented method for correcting residual optical defects in an image acquired by a camera with a given focal length, the acquired image being calibrated, the residual optical defects being relative to the given focal length, the method comprising: • To obtain a correction of residual optical defects in the acquired image, the Correction dependent: • a first calibration table corresponding to an amplitude of the residual optical defects at the given focal length and; • a first adaptation factor between the first calibration table and the acquired image, • Obtain a second image corrected for residual optical defects from the calibrated acquired image and the correction, by subtracting the correction from the acquired image.

[0026] The term "acquired image having been calibrated" refers to an image to which a calibration method, such as point calibration, has been applied. Thus, on a calibrated image, the intrinsic defects of the camera detector are corrected. In particular, if the offset table of the calibration method was obtained from a diaphragm in front of a specific optical field, all defects of the type "optical reflection" or "parasitic defects" are also corrected only in the calibration field and not in other fields. If the offset table is obtained by defocusing, defects of the type "optical reflection" or "parasitic defects" are not corrected in any field. Thus, optical reflection defects or parasitic optical defects are referred to hereafter as residual optical defects.

[0027] In particular, "optical reflection" or "parasitic defects" are Narcissus defects, resulting from non-uniformities created by parasitic heat fluxes emitted by the camera detector. These non-uniformities are reflected off at least one lens of the camera and imaged on the detector. Residual optical defects depend on the field of view (or equivalently, the focal length) of the camera. Residual optical defects are distinct from the intrinsic defects of the camera detector and are modeled as additive spatial noise. Thus, residual optical defects are present in the image acquired after calibration.

[0028] In particular, a given field of view of the camera corresponds to a given focal length F'd of the camera lens. The given field of view is defined by an angle called the field angle ad, expressed according to the following formula: ad = 2*arctan( _A_), with d the length of an edge or a diagonal of an image acquired by the camera.

[0029] Thanks to the invention, residual optical defects in an acquired and calibrated image are corrected using the first calibration table associated with the same field (or equivalently, the same focal length) as that of the image acquired and calibrated at the factory, for example. In particular, the adaptation factor allows the amplitude of the first calibration table to be adjusted in order to bring the residual optical defects of the acquired image closer to the residual optical defects calibrated at the factory. The first adaptation factor can take into account the camera integration time during the acquisition of the image to be corrected and the time used at the factory for the calibration table, the amplitude of the residual optical defects dependent on integration time, for example. Thus, the invention allows for an increase in the quality of information reproduction of the acquired image by homogenizing the acquired image, unlike the prior art in which only defects due to the detector pixels are corrected. The reading of the acquired image by a user is improved, and details are more visible when it is necessary to observe a distant target, for example. Advantageously, the invention makes it possible to eliminate any optical defect modeled as additive spatial noise in the field under consideration, regardless of its shape or geometry, without altering the acquired image.

[0030] In addition to the features mentioned in the preceding paragraph, the method according to one aspect of the invention may have one or more complementary features from the following, considered individually or in all technically possible combinations.

[0031] According to one embodiment, the correction comprises a product of the first adaptation factor and the first calibration table.

[0032] According to one embodiment, the residual optical defects are parasitic heat flux defects associated with the given focal length and are modeled by spatial additive noise. Advantageously, any optical defect relative to a given focal length and modelable by spatial additive noise can be corrected by the invention.

[0033] According to one embodiment: • The first calibration table is associated with a camera calibration integration time and a camera calibration internal temperature, and • The image is acquired for a given camera integration time and for a given camera internal temperature, and the first adaptation factor is determined from the calibration integration time, the given integration time, the calibration internal temperature, and the given camera internal temperature. The first adaptation factor is determined from the calibration integration time, the given integration time, the calibration internal temperature, and the given internal temperature. Advantageously, the first adaptation factor allows for consideration of the different acquisition conditions of the image to be corrected and the calibration table. In particular, the first adaptation factor takes into account the camera integration time, on which the magnitude of residual optical defects depends. Thus, the first adaptation factor varies when the integration time varies.

[0034] According to one embodiment, the first adaptation factor is defined as a product: From a ratio of the given integration time and the integration time calibration, and • A ratio of the given internal temperature and the calibration internal temperature.

[0035] According to one embodiment, the first adaptation factor is defined as a product: • From a ratio of the given integration time and the calibration integration time, and • Of a ratio of a luminance obtained from the given internal temperature and a luminance obtained from the calibration internal temperature.

[0036] According to one embodiment, the correction also depends on: • a second calibration table corresponding to a variation in the amplitude of residual optical defects as a function of a variation in the camera's internal temperature for the given focal length, and • a second adaptation factor between the second calibration table and the acquired image.

[0037] According to one embodiment, the first calibration table is associated with a camera calibration integration time and a camera calibration internal temperature, and the image is acquired for a given camera integration time and a given camera internal temperature, and according to which: • The first adaptation factor is determined from the calibration integration time and the given integration time. • The second adaptation factor is determined from the first adaptation factor, the given internal temperature, and the calibration internal temperature.

[0038] According to one embodiment, the first calibration table is associated with a camera calibration integration time and a camera calibration internal temperature, and the image is acquired for a given camera integration time and a given camera internal temperature and: • The first adaptation factor is determined from the calibration integration time and the given integration time. • The second adaptation factor is determined from the first factor, a luminance obtained from the given internal temperature, and a luminance obtained from the calibration internal temperature.

[0039] According to one embodiment, the first adaptation factor and the second adaptation factor are respectively equal to a first initial value and a second initial value, and obtaining the correction comprises: • Obtain an intermediate image by subtracting an inter- correction median to the acquired image, the intermediate correction being determined from the first adaptation factor equal to the first initial value, the first calibration table, the second adaptation factor equal to the second initial value and the second calibration table, • Optimization of a criterion relating to the intermediate image, by obtaining a first optimal adaptation factor and a second optimal adaptation factor, the correction of residual optical defects being determined from the first optimal adaptation factor and the second optimal adaptation factor.

[0040] According to one embodiment, the residual optical defects are modeled as a radial geometry defect, and the optimization criterion includes a step of applying a filter adapted to the radial geometry of the defect to the intermediate image to obtain a filtered intermediate image. The criterion corresponds to a variance of the filtered intermediate image. For example, the filter adapted to the radial geometry is a gradient filter or a Laplacian filter.

[0041] Another aspect of the invention relates to a computer program product comprising instructions which, when the program is executed by a computer, lead the computer to implement the method according to the invention.

[0042] Another aspect of the invention relates to a computer-readable medium comprising instructions which, when executed by a computer, lead the computer to implement the method according to the invention.

[0043] The invention and its various applications will be better understood by reading the following description and examining the accompanying figures. BRIEF DESCRIPTION OF THE FIGURES

[0044] The figures are presented for illustrative purposes only and are in no way limiting of the invention.

[0045] The [Fig. 1] is a uniform graph of the temperature T of the parasitic flux received by the detector on the pixels Pi_c of the center line of the detector in the prior art.

[0046] The [Fig.2] is a non-uniform graph of the temperature T of the parasitic flux received by the detector on the pixels Pi_c of the center line of the detector in the prior art.

[0047] Fig. 3 represents the responses of two pixels to a luminance from a thermal flux, corresponding to graphs of the grey levels at the level of each pixel as a function of the luminance received by the pixel in the prior art.

[0048] Fig. 4 is a synoptic diagram representing a state-of-the-art method for correcting non-uniform defects on an image corresponding in particular to detector defects.

[0049] Fig. 5 is a synoptic diagram representing the steps of a method for determining the first calibration table.

[0050] Fig. 6 is a synoptic diagram representing the steps of a method for determining the second calibration table.

[0051] Fig. 7 is a synoptic diagram representing the steps of a correction method according to the invention.

[0052] The [Fig.8] is a synoptic diagram representing the sub-steps of a step in determining a correction of residual optical defects of the correction method according to the invention.

[0053] Figure [Fig.9] represents three graphs corresponding to an amplitude of optical defects on the central line of an image.

[0054] The [Fig. 10] is a diagram representing a device configured to implement the method according to the invention. DETAILED DESCRIPTION

[0055] The invention relates to a method for correcting residual optical defects in an image acquired by an infrared camera, preferably the infrared camera having a detector cooled to a constant temperature.

[0056] The camera is located for example in an aircraft or in an observation sight located in a land vehicle and acquires for example images which can be displayed in real time or later to a user of the aircraft or land vehicle for example.

[0057] An "infrared camera" is defined as a camera configured to measure and record heat waves and infrared radiation emitted by a body or object, in order to generate sequences of images known as infrared images. The camera is, for example, a Short-Wave Infrared (SWIR), Long-Wave Infrared (LWIR), or Midwave Infrared (MWIR) camera.

[0058] In particular, the camera includes a zoom lens, that is, a lens with a variable focal length that can be adjusted by the user. In the following, "focal length" and "focal angle" will be used interchangeably. As described previously, the camera's field of view is inversely proportional to the focal length.

[0059] In particular, the infrared camera includes an infrared detector, formed for example of an array of FPA (Focal Plane Array) type detectors.

[0060] In particular, the images acquired by the camera can be greyscale images.

[0061] During the acquisition of an image of a scene by the camera, the image includes parasitic optical defects or reflection defects resulting from the detector, the defects depending on the camera's field of view. In particular, the camera lens includes a front lens onto which parasitic optical heat fluxes from the camera's cooled detector are reflected and imaged on said detector. When The lens configuration is modified to change the lens focal length and therefore the camera's field of view. This alters the optical path of stray light, which in turn changes its impact on the image acquired by the camera. In other words, optical defects resulting from stray heat flux are focal length dependent and therefore vary as the focal length changes. These optical defects are called parasitic optical defects or internal reflection optical defects and can have any geometry, such as radial or square. In particular, the geometry of parasitic optical defects exhibits rotational symmetry.

[0062] For example, when the camera is calibrated using Method 100, the steps of which are shown in [Fig. 4] and described previously, internal reflection optical defects (due to the detector) are corrected for a given field of view if the shuttering is performed by a diaphragm, or are not corrected (because they are not visible) if the shuttering is performed by defocusing. Thus, as described previously, since internal reflection optical defects depend on the camera's field of view, the one-point calibration method described in Method 100 cannot eliminate them if the offset table was obtained for a different field of view or was obtained by defocusing (and not by using a physical diaphragm).

[0063] The offset table used in the one-point calibration method and the real-time acquired image are each obtained for a camera integration time and an internal camera temperature that may be equal to or different from the internal temperatures and camera integration time respectively during real-time image acquisition.

[0064] In particular, the amplitudes of the internal reflection optical defects of the detector vary as a function of the internal temperature and the integration time of the camera.

[0065] The term "internal camera temperature" refers to the temperature acquired near the optics of the camera lens, and in particular near the front lens of the lens, for example. In the following, any value of the internal camera temperature is, for example, within the range [-20; +70] °C.

[0066] In the following text, optical reflection defects present in an image after calibration, particularly after the application of a one-point calibration method, are referred to as residual optical defects. The correction method according to the invention thus aims to correct these residual optical defects for each given focal length F'd and each temperature and integration time, without having to repeat a one-point calibration method (method 100). According to the invention, the correction of these defects is performed using a first calibration table Old and a second calibration table O2d, each calibration table being associated with the given focal length F'd.

[0067] The first Old calibration table associated with the given focal length F'd has the same size that the size of a matrix of the camera detector, and therefore the same size as the image to be corrected, and corresponds to a matrix of amplitudes of the residual optical defects for the given focal length F'd. In particular, each coefficient of the first calibration table corresponds to an amplitude of the residual optical defects for a given position of a pixel of the camera detector.

[0068] The second calibration table O2d has the same size as the size of the camera detector matrix, and therefore the same size as the image to be corrected, and corresponds to a matrix modeling variations in the amplitudes of the residual optics as a function of the internal temperature variations of the camera for the given focal length F'd. In particular, each coefficient of the second calibration table corresponds to a value of variation in the amplitude of the residual optical defects for a given position of a pixel of the camera detector.

[0069] Examples of determining the first and second calibration tables are described in the following text.

[0070] In particular, for each focal length F'i, the first calibration table Oh associated with the focal length F'i can be determined according to a method for determining the first calibration table. Figure 5 shows a block diagram of the steps of the method for determining the first calibration table Oh associated with the focal length F'i. In particular, each calibration table Oh is associated with the internal calibration temperature of the camera and the calibration integration time of the camera.

[0071] The method 200 includes a step 201 of acquisition by the camera of an image Isj of a thermal flux emitted by a homogeneous and isotropic source, for the focal length F'i of the camera, the internal calibration temperature Tétaionnage of the camera and the calibration integration time Tétaionnage of the camera which are stored by a user in a memory external to the camera for example.

[0072] A "homogeneous and isotropic source" is understood to be a source emitting, for example, a heat flux (or thermal radiation) similar to the heat flux emitted by a black body, that is to say, a homogeneous and isotropic heat flux, the radiation of which depends only on the temperature and not, for example, on directions in space. Advantageously, the use of a source emitting isotropic radiation makes it possible to have a homogeneous scene and to observe only the optical defects of the camera.

[0073] In practice, the source can be a heating plate entirely covered with black paint, and having a uniform, constant temperature that can be adjusted by a user. Thus, the source can be considered a black body.

[0074] The thermal flux emitted by the source covers the entire pupil of the camera lens.

[0075] Method 200 includes a step 202 of calibrating the image Isj according to the Method 100 involves a one-point camera calibration in which the shutter step corresponds to a defocusing step. This corrects the intrinsic defects of the detector but does not correct its reflection defects. The one-point calibration is performed using the gain table G and the offset table O described previously. After the calibration step, an image of the calibrated source IS2_i is obtained from the image of the source IS i, such that: Is2j = - O

[0076] The IS2jobtenue image corresponds to the image of the source Isj corrected for detector defects and includes residual optical defects as mentioned above, i.e. residual optical defects corresponding to parasitic thermal fluxes of the camera lens relative to the focal length F';.

[0077] Method 200 further includes a step 203 of obtaining a third image IS3_i resulting from the subtraction of an average image of the image IS2j, denoted Average(IS2j), from the calibrated image IS2j. In particular, Average(IS2j) corresponds to an image of the same size as IS2j and in which each coefficient corresponds to the average of all the pixel values ​​of IS2j.

[0078] Thus, IS3J = IS2 t - Average(lS2j)-

[0079] According to a first embodiment, the first calibration table OL associated with the focal length F'i corresponds to IS3 jet can therefore be noted: Olj = IS3_i.

[0080] Thus, the first OL calibration table can be obtained at the end of step 203.

[0081] According to a second embodiment, method 200 comprises a step 204 op spatial filtering of the third image IS3j to obtain a filtered image F(I S3j)*

[0082] The filtering can, for example, correspond to a spatial filtering of the IS3j image in the case where intrinsic defects of the detector remain even after the calibration step 201, for example due to one or more defective pixels of the detector. In this second embodiment, the first calibration table Ol; can be equal to F(Is3_i).

[0083] According to a third embodiment, the first calibration table O h is obtained at the end of optional steps not shown in method 200, described below.

[0084] Method 200 may include an optional first step of carrying out steps 201, 202 and 203 at several different times t and obtaining a plurality of images (IS3_it)t>o

[0085] Method 200 may include an optional second step of averaging the IS3i_t images to obtain an average image Average(IS3 it)t>o- In particular, the averaging step 206 corresponds to averaging each pixel value of each IS3jt image having the same position in the image. In other words, each coefficient at a given position of the image Average(IS3 it)t>o corresponds to an average of the pixel values ​​of the same position of each image Is3_it-

[0086] Method 200 may include an optional third step of obtaining the first calibration table O h by subtracting the image Mean(IS3_it) from the image I S3_if Thus, Olâ = IS3i - Mean(IS3it).

[0087] In particular, the third embodiment advantageously makes it possible to remove temporal noise present in the IS3j image, temporal noise degrading the quality of the image by giving it a grainy appearance.

[0088] According to an embodiment not shown, the optional steps are applied to the image F(IS3_i) following step 204.

[0089] Method 200 for obtaining the first calibration table Δl associated with the focal length F'i can be performed for a plurality of M focal lengths πr'j, thus obtaining M first calibration tables (Ql), each associated with a different focal length F'i, the index i being a natural number. In particular, each first calibration table among the M first calibration tables is obtained for a different focal length but with the same internal calibration temperature of the camera and the same calibration integration time of the camera.

[0090] In particular, each first calibration table can be compressed before being saved in memory for use. The compression method must be adapted to the spatial morphology of the residual optical defects represented by each first calibration table, in order to avoid any degradation of the quality of the first calibration table.

[0091] Regarding the second calibration table O2, for each focal length F'i, the second calibration table O2 associated with the focal length F'i can be determined according to a method for determining the second calibration table. Figure 6 shows a block diagram of the steps of method 300 for determining the second calibration table O2i associated with the focal length F'i. In particular, each calibration table O2 is associated with the camera calibration integration time.

[0092] Method 300 includes a step 301 of acquisition by the camera of a first image IlSj of a thermal flux emitted by the source defined in the method for determining the first calibration table. In particular, the acquisition step 301 is carried out for the focal length F' of the camera, at an internal calibration temperature Tl of the camera and with the calibration integration time of the camera, which are stored by a user in an external memory for example or in a memory of the camera.

[0093] Method 300 further includes a step 302 identical to step 202, step 302 being applied to the Ilsj image and allowing the calibrated image IlS2_i to be obtained. The calibrated image IlS2_i corresponds to the Ils_i image corrected for detector defects and comprising residual optical defects as described previously. Residual optical defects correspond to parasitic heat fluxes from the camera lens for the focal length F';.

[0094] Method 300 further includes a step 303 of obtaining an image IlS3j resulting from the subtraction of an average image of the image IlS2j, denoted Average(IlS2_i), from the calibrated image IlS2j. In particular, Average(IlS2j) corresponds to an image of the same size as IlS2j and in which each coefficient corresponds to the average of all the pixel values ​​of IlS2_i. Thus, IlS3_i J1S2 j - Average(IlS2j)-

[0095] Method 300 further includes a step 304 of varying the internal temperature of the camera, to obtain an internal temperature T2saturation of the camera different from Tsaturation. The variation of the camera's internal temperature can be achieved by placing the camera in a temperature-adjustable oven, for example.

[0096] Method 300 includes a step 305 of acquisition by the camera of a second image I2Sj of the heat flux source defined in method 200, for the focal length F'i of the camera, the internal calibration temperature T2etaionnage of the camera and the calibration integration time tetaionnage of the camera.

[0097] Method 300 further includes a step 306 identical to step 202, step 306 being applied to the image I2Sj and allowing the calibrated image I2S2_i to be obtained. The calibrated image I2S2j corresponds to the image I2s_i Corrected for detector defects and including residual optical defects as mentioned above.

[0098] Method 300 further includes a step 307 of obtaining an image rS3j resulting from the subtraction of an average image of the image I2S2j, denoted Average(I2S2_i) from the calibrated image I2S2_i. In particular, Average(I2S2j) corresponds to an image of the same size as I2S2_i and whose coefficient corresponds to the average of all the pixel values ​​of I2S2j. Thus, I2S; . = 12s2i - Average(12S2i).

[0099] Method 300 includes a step 308 of obtaining the second calibration table O2; from the image IlS3j, the calibration temperature Tlétaionnage, the image I2S3_i and the calibration temperature T2étaionnage.

[0100] In particular, the second calibration table O2 allows for the estimation of the variation of residual optical defects as a function of the variation in internal temperature. An interpolation is performed between the variation of residual optical defects and the variation in internal temperature, the interpolation order being chosen according to predetermined criteria. Indeed, the higher the interpolation order, the better the quality of the images to be corrected for residual optical defects, because the relationship between the variation of residual optical defects and the variation in internal temperature is more precise. However, the higher the interpolation order, the more complex the method is to implement, as a plurality of blackbody image acquisitions is required.

[0101] In particular, the variation of residual optical defects can depend linearly and indirectly on the variation of luminance due to temperature variation. Indeed, the variation of residual optical defects depends linearly on the variation of luminance, which depends on temperature.

[0102] Thus, the second O2 calibration table is obtained according to the following formula: Q2 — Hs3_i“I2s3j , with L(T1 étaionnage) the integrated luminance generated by L(T létaIoniiage)'^^2étaIonnage) temperature Tlétaionnage and L(T2étaionnage) the integrated luminance generated by the temperature T? A -^calibration*

[0103] Thus, the integrated luminance is related to the internal temperature T that the camera integrates (captures). The gray level captured by the camera depends on a multitude of sources. For interpolation purposes, a simulation of the variation of gray levels captured by the detector as a function of the variation of the internal temperature is performed. The determination of the luminance as a function of temperature (denoted L(T1) and L(T2)) is obtained, for example, via a simulation method of the infrared camera.

[0104] In particular, the integrated luminance takes into account a fixed temperature T of a scene integrated by the camera and passing through the optics, the internal luminance of the camera (i.e. the photons leaving the camera and reaching the detector) and the dark current of the camera detector.

[0105] When the infrared camera is placed in front of a scene with a fixed temperature T, the internal temperature of the camera is varied in order to observe the evolution of the variation of the grey level as a function of the variation of the internal luminance of the camera.

[0106] The integrated luminances are obtained from a resolution of Planck's equations in a context applied to the camera, i.e. taking into account the variation of grey level as a function of the variation of the internal luminance of the camera.

[0107] Using luminance values ​​as a function of temperature is advantageous because the luminance of a pixel in an image is modeled linearly with respect to its gray level, for any temperature. Thus, since luminance is linear with gray levels, the simulation is valid for all temperatures.

[0108] Method 300 for obtaining the second calibration table O2 associated with the focal length F'i can be carried out for a plurality of M focal lengths / p 3, which makes it possible to obtain M second calibration tables / Q2 j each associated with a focal length different F';. In particular, each first calibration table among the first M calibration tables is obtained for a different focal length but with the same camera calibration integration time.

[0109] Thus, method 200 shown in [Fig. 5] and method 300 shown in the [Fig.6] allow respectively to obtain first and second calibration tables used in method 400 of correction of residual optical defects according to the invention, the steps of which are represented in [Fig.7].

[0110] Figure 7 presents a block diagram of Method 400 for correcting residual optical defects according to the invention. In particular, Method 400 aims to correct the residual optical defects of an Imd image acquired for a given focal length F'd by the camera described above, and corrected for detector defects using, for example, the one-point calibration method.

[0111] The hnd image to be corrected for residual optical defects is acquired by the camera for an integration time td and an internal temperature Td, stored in a memory of the camera or an external memory to the camera for example.

[0112] In particular, in order to correct these residual optical defects, the first Old calibration table associated with the given focal length F'd is used in method 400.

[0113] In addition, the second calibration table O2d associated with the given focal length F'd is used in method 400.

[0114] The correction method 400 includes a step 401 of obtaining a correction Corrd of the residual optical defects of the image Imd, from the first calibration table O ld and the second calibration table O2d. The correction Corrd is an image of the same size as the image to be corrected, determined from the first calibration table Old, a first adaptation factor Kld relative to the first calibration table Old, the second calibration table O2d and a second adaptation factor K2d relative to the second calibration table O2d.

[0115] In particular, the first adaptation factor Kld allows the amplitude of the first calibration table Old to be adjusted to the image to be corrected, the first calibration table Old and the image Imd to be corrected each having the amplitude of the residual optical defects for the focal length F'd but for different acquisition conditions. The first adaptation factor Kld is a real number strictly greater than 0.

[0116] In particular, the second adaptation factor K2d allows the amplitude of the second calibration table O2d to be adjusted to the image to be corrected, in order to take into account the effects of internal camera temperature variations on the amplitude of residual optical defects. The second adaptation factor K2d is a real number strictly greater than 0.

[0117] For example, the Corrd correction is equal to Kld* Old+ K2d* O2d in the case of a first-order interpolation

[0118] In particular, the first adaptation factor Kld and the second adaptation factor K2d can be obtained according to several embodiments described below.

[0119] In a first embodiment of obtaining the Corrd correction, the variation the amplitude of the residual optical defects of the internal temperature of the camera is modeled as uniform over the entire image to be corrected and all the coefficients of the second calibration table O2d are thus equal to 1. In this embodiment, the second adaptation factor K2d is zero.

[0120] Thus, Corrd = Kld * Old. In this first embodiment, the optical defects to be corrected in the image have a deterministic formula for calculating their amplitude, which corresponds to the reflection of the detector on the optics (commonly called the Narcissus effect). The deterministic formulas are based on the physical nature of the residual optical defects.

[0121] In this first embodiment, the first Olda calibration table was obtained for the integration time and the internal temperature of the camera. first adaptation factor Kld depends on the sizing, sizing, the integration time td of the camera during the acquisition of the image to be corrected, the internal temperature Td of the camera during the acquisition of the image to be corrected.

[0122] In particular, we consider the following quantities: L(Tetation), the luminance integrated by the camera for an object having a temperature Tetation and L(Td) the luminance integrated by the camera for an object having a temperature Td. Kld can be equal to U'L)__L . T / TV calibration 1 calibration /

[0123] In particular, as previously stated, for any temperature T, the luminance L as a function of temperature T is obtained according to Planck's formula.

[0124] In particular, in this first embodiment, Kld can be equal to a function or a polynomial of the parameter, for example, the polynomial being preferably 1 calibration of order m greater than or equal to 2.

[0125] In a second embodiment of obtaining the Corrd correction, the variation in the amplitude of the residual optical defects due to the camera's internal temperature is modeled as non-uniform across the entire image to be corrected. Thus, the first adaptation factor Kld and the second adaptation factor K2d are not null, and the second calibration table O2d includes coefficients not necessarily equal to 1. In this second embodiment, the optical defects to be corrected in the image have a deterministic formula for calculating their amplitude, which corresponds to the reflection from the detector on the optics (corresponding to the Narcissus effect). The deterministic formulas are based on the physical nature of the residual optical defects.

[0126] In this second embodiment, Kld is for example equal to k and K2dest ^ét«donnage for example equal to LÇTj td = UTd) Kld T CT ï ^calibration T (T | calibration / w calibration /

[0127] In a third embodiment, step 401 of obtaining the correction Corrd It includes substeps 4011 and 4012 shown in [Fig. 8]. In this embodiment, the factors Kld and K2d have an arbitrary initial value, for example, 0. This embodiment allows for the correction of optical defects for which there are no formulas to calculate their amplitudes, such as vignetting. This embodiment can also be used for the Narcissus effect.

[0128] Substep 4011 is a step for obtaining an intermediate image Im(interm)d' = Imd - Corrdinterm, with Corrdinterm an intermediate correction equal to (Kld*Old + K2d * O2d), with the factors Kld and K2 equal to their respective initial values ​​Kld0 and K2d_0.

[0129] Substep 4012 is an optimization step for the first factor Kld and the second factor K2d in order to reduce a criterion on the image Im(interm)d'. In particular, substep 4012 makes it possible to find optimal values ​​respectively for Kld and K2d, also denoted Kld opt and K2doptt such that the criterion on the image Im(interm)d' is satisfied.

[0130] For example, if the residual optical defects are modeled as low-frequency additive spatial noise, the image Im(interm)d' is filtered to eliminate high frequencies and the criterion to be reduced or even minimized is a variance of the filtered image Im(interm)d', which makes it possible to minimize the effects of the residual optical defects.

[0131] In particular, the image Im(interm)d is spatially filtered so as to eliminate any defects that may be present other than optical reflection defects. It is necessary that the filtering does not alter said optical reflection defects.

[0132] Optical reflection defects can be spatially high-frequency (HF) in nature, spatially low-frequency (LF) in nature, or, for example, a mixture of both. Therefore, in typical cases, conventional high-frequency or low-frequency filtering via a convolution matrix, for example, is not optimal.

[0133] In particular, optical reflection defects are defects having rotational symmetry. If the optical reflection defects have a radial geometry with rotational symmetry, an example of a spatial filter is a radial filter that will retain only the spatial frequencies having rotational symmetry.

[0134] In particular, the optimization is carried out for example using the gradient descent algorithm.

[0135] Thus, at the end of step 4012 optimal values ​​are obtained for the first factor Kld and for the second factor K2d, such that the condition on the image criterion Im(interm)d' is respected.

[0136] With further reference to [Fig. 7], method 400 includes a step 402 of correction of residual optical defects in the acquired Imd image.

[0137] The correction step 402 is carried out by subtracting the correction Corrd from the image Imd, to obtain an image Imd' corrected for residual optical defects. Thus, Imd' is equal to Imd - Corrd.

[0138] Thus, the user observes the Im / image of better quality than the Imd image and free from residual optical defects.

[0139] Figure 9 represents three graphs of the amplitudes of defects present in a central line of an image. The ordinate axis thus represents the amplitude of the defects in an image and the abscissa axis represents the pixels Pi_c of the central line of the image.

[0140] In particular, a first graph represents the amplitude of defects in a central line of an IM image acquired by the camera, without any correction. This includes defects due to the detector and optical defects due to parasitic fluxes from the camera optics.

[0141] A second graph represents the magnitude of defects in an IM' image, obtained using a one-point calibration method applied to the IM image. Thus, the magnitude of the defects has decreased compared to the first graph, as the detector defects have been eliminated. However, residual optical defects, as described above, remain.

[0142] A third graph represents the amplitude of the defects in an IM image obtained after applying the residual optical defect correction method according to the invention. Thus, the amplitude of the optical defects is uniform and approaches zero, unlike the other graphs. Therefore, the correction method according to the invention effectively reduces or even eliminates residual optical defects in the acquired images.

[0143] Another aspect of the invention relates to a device configured to implement the method of correcting residual optical defects of an image according to the invention.

[0144] Figure 10 represents the device according to the invention, according to one or more embodiments of the invention.

[0145] In these embodiments, the device includes a computer 500, comprising a memory 501 for storing instructions which, when implemented by a processor of the computer, lead the processor and therefore the computer to implement the correction method.

[0146] The computer 500 further comprises a circuit 502. This circuit can be, for example, a processor capable of interpreting instructions in the form of a computer program, an electronic card whose steps of the method of the invention are described in silicon, or a programmable electronic chip such as an FPGA chip (for "Field-Programmable Gate Array" in English).

[0147] The computer 500 includes an input interface 503 for receiving the image acquired by the camera, for example, corrected for detector defects, and an output interface 504 for providing the image corrected for residual optical defects, for example. Finally, the computer may include, to allow easy interaction with a user, a screen 505 and a keyboard 506. Of course, the keyboard is optional, particularly in the case of a computer in the form of a touchscreen tablet, for example.

[0148] Of course, the present invention is not limited to the embodiments described above by way of example; it extends to other variants.

Claims

1.

2.

3.

4. Claims A computer-implemented method (400) for correcting residual optical defects in an image (Imd) acquired by a camera with a given focal length (F'd), the acquired image (Imd) being calibrated, the residual optical defects being relative to the given focal length (F'd), the method (400) comprising: - Obtain (401) a correction (Corrd) of the residual optical defects of the acquired image (Imd), the correction (Corrd) depending on: • a first calibration table (01 d) corresponding to an amplitude of the residual optical defects at the given focal length (F'd) and; • a first adaptation factor (Kld) between the first calibration table (Old) and the acquired image (Imd), - Obtain (402) a second corrected image (Im'd) of the residual optical defects from the acquired calibrated image (ImJ) and the correction (Corrd), by subtracting the correction (Corr d) from the acquired image (Imd). Method (400) according to the preceding claim according to which the correction (Corrd) comprises a product of the first adaptation factor (Kld) and the first calibration table (Old). Method (400) according to one of the preceding claims according to which the residual optical defects are parasitic thermal flux defects associated with the given focal length and are modeled by spatial additive noise. Method (400) according to any one of the preceding claims wherein: - the first calibration table (Old) is associated with a calibration integration time (tetaiOnnage) of the camera and an internal calibration temperature (TetaiOnnage) of the camera and, - the image (Imd) is acquired for a given integration time (td) of the camera and for a given internal temperature (Td) of the camera, and according to which the first adaptation factor (Kld) is determined from the calibration integration time (Td), the given integration time (td), the calibration internal temperature (Td) and the given internal temperature (Td) of the camera.

5. Method (400) according to the preceding claim according to which the first adaptation factor (Kld) is defined as a product: - Of a ratio of the given integration time (td) and the calibration integration time (Testing), and - Of a ratio of the given internal temperature (Td) of the camera and the internal temperature (Testing) of calibration.

6. Method (400) according to claim 4 according to which the first adaptation factor (Kld) is defined as a product: - Of a ratio of the given integration time (td) and the calibration integration time (Tetration), and - Of a ratio of a luminance (L(Td)) obtained from the given internal temperature (Td) of the camera and of a luminance (L(Tetration)) obtained from the calibration internal temperature (Tetration).

7. Method according to any one of claims 1 to 3 according to which the correction (Corrd) further depends on: - a second calibration table (O2d) corresponding to a variation in the amplitude of the residual optical defects as a function of a variation in the internal temperature of the camera for the given focal length F'd and; - a second adaptation factor (K2d) between the second calibration table (O2d) and the acquired image (Imd).

8. Method (400) according to the preceding claim according to which the first calibration table (Old) is associated with a calibration integration time (Tetration) of the camera and with an internal calibration temperature (Tetration) of the camera, and the image (Imd) is acquired for a given integration time (td) of the camera and a given internal temperature (Td) of the camera and according to which: - the first adaptation factor (Kld) is determined from the calibration integration time and the given integration time, - the second adaptation factor (K2d) is determined from the first adaptation factor (Kld), the given internal temperature (Td) and the calibration internal temperature (Test).

9. Method (400) according to claim 7 according to which the first calibration table (Old) is associated with a calibration integration time (t calibration) of the camera and with an internal calibration temperature (T calibration) of the camera, and the image (Imd) is acquired for a given integration time (td) of the camera and a given internal temperature (Td) of the camera and according to which: - the first adaptation factor (Kld) is determined from the calibration integration time and the given integration time, - the second adaptation factor (K2d) is determined from the first adaptation factor (Kld), a luminance (L(Td)) obtained from the given internal temperature (Td) and a luminance (L(Tetration)) obtained from the calibration internal temperature (Tetration).

10. Method (400) according to claim 7 according to which the first adaptation factor (Kld) and the second adaptation factor (K2d) are respectively equal to a first initial value (Kld 0) and a second initial value (K2d 0) and according to which the obtaining (401) of the correction comprises: - Obtain (4011) an intermediate image Im(interm)d' by subtracting an intermediate correction (Corrd interm) from the acquired image, the intermediate correction (Corrd interm) being determined from the first adaptation factor (Kld) equal to the first initial value (Kld 0), the first calibration table (Old), the second adaptation factor (K2d) equal to the second initial value (K2d 0) and the second calibration table (O2d), - Optimization (4012) of a criterion relating to the intermediate image Im(interm)d', by obtaining a first optimal adaptation factor (Kldopt) and a second optimal adaptation factor (K2dopt), the correction of residual optical defects being determined from the first optimal adaptation factor (Kld _opt) and the second optimal adaptation factor (Kld opt).

11. Method (400) according to the preceding claim according to which the residual optical defects are modeled as a radial geometry defect and the optimization of the criterion comprises a step of applying a filter adapted to the radial geometry of the defect to the intermediate image to obtain a filtered intermediate image and the criterion corresponds to a variance of the filtered intermediate image.

12. A computer program product comprising instructions which, when the program is executed by a computer, cause the latter to implement the method according to one of claims 1 to 10.

13. A computer-readable medium comprising instructions which, when executed by a computer, cause the computer to implement the method of one of claims 1 to 10.

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