Electronic endoscope processor and electronic endoscope system

Abstract

To acquire a sufficient edge emphasis image suitable for endoscope observation as compared with conventional techniques when acquiring a picked-up image of a biological tissue and subjecting the image to edge emphasis processing.SOLUTION: One embodiment of the present invention is a processor for an electronic endoscope for acquiring a picked-up image of a biological tissue and subjecting the image to emphasis processing. The processor includes: a separation unit for separating the information on an RGB color space of the picked-up image of the biological tissue into a color difference component and a luminance component; a feature component extraction unit for extracting a feature component including at least one of a G component and a B component from the information on the RGB color space of the picked-up image; an edge component extraction unit for extracting an edge component from the feature component; an addition unit for executing predetermined weighting for the edge component and adding the edge component to the luminance component; and a conversion unit for converting the color difference component and the luminance component acquired by the addition unit into the information on the RGB color space.SELECTED DRAWING: Figure 6

Description

[Technical Field]

[0001] The present invention relates to an electronic endoscope processor and an electronic endoscope system for acquiring and enhancing images of biological tissue. [Background technology]

[0002] Electronic endoscopes are used for observing and treating biological tissues inside the human body. Images obtained using these electronic endoscopes are then enhanced to highlight specific elements of the tissue, and these enhanced images are displayed on a screen.

[0003] An endoscope system is known that can enhance the edges of each luminance signal without emphasizing noise components by referencing the luminance signals of pixels over a wide range and removing noise by referencing the luminance signals of pixels in a minute range (Patent Document 1). This endoscope system includes: noise reduction means for generating a noise reduction signal for a pixel of interest using the luminance signals of the pixel of interest and first peripheral pixels located around the pixel of interest in a minute region; edge enhancement means for detecting wide-area edge components of the pixel of interest using the luminance signals of the pixel of interest and second peripheral pixels located around the pixel of interest in a wider area than the minute region; and addition means for generating a processed luminance signal for the pixel of interest by adding the noise reduction signal and the wide-area edge components. [Prior art documents] [Patent Documents]

[0004] [Patent Document 1] Patent No. 4801626 [Overview of the project] [Problems that the invention aims to solve]

[0005] In the edge enhancement means for the endoscope system described in Patent Document 1, as shown in Figure 2, after converting the RGB signal of the captured image to YC, only the luminance signal (Y) is edge-enhanced, and the chrominance signal (Yc, Yr) is not edge-enhanced. In other words, the information that forms the basis of edge enhancement is limited to the Y component of the YCbCr color space.

[0006] However, in endoscopic observation, it is necessary to emphasize features with strong redness, such as blood vessels and redness. Edge enhancement methods that apply edge enhancement only to the brightness signal sometimes fail to produce sufficiently edge-enhanced images suitable for endoscopic observation.

[0007] Therefore, the present invention aims to provide an electronic endoscope processor and an electronic endoscope system that can obtain sufficiently edge-enhanced images suitable for endoscopic observation compared to conventional methods when acquiring imaging images of biological tissue and applying edge enhancement processing. [Means for solving the problem]

[0008] One aspect of the present invention is an electronic endoscope processor that acquires and enhances images of biological tissue. This processor is A separation unit that separates the RGB color space information of an image of biological tissue into color difference components and luminance components, A feature component extraction unit extracts feature components from the RGB color space information of the captured image, which include at least one of the G component and the B component. An edge component extraction unit that extracts edge components from the aforementioned characteristic components, An addition unit that applies a predetermined weight to the edge component and adds it to the luminance component, The system includes a conversion unit that converts the color difference component and the luminance component obtained by the addition unit into information in the RGB color space.

[0009] The aforementioned feature component may be information in which a positive weight is given to at least one of the G component and the B component of the RGB color space information of the captured image.

[0010] The feature component extraction unit extracts a plurality of the feature components, The edge component extraction unit extracts an edge component from each of the plurality of the feature components, The addition unit may perform predetermined weighting on each of the extracted edge components and add them to the luminance component.

[0011] The plurality of the feature components include a first feature portion composed of the R component of the captured image and a second feature portion having the G component and the B component of the captured image, The edge component extraction unit extracts a first edge component from the first feature portion and extracts a second edge component from the second feature portion, The addition unit may perform negative weighting on the first edge component and positive weighting on the second edge and add them to the luminance component.

[0012] Another aspect of the present invention is an endoscope system including the endoscope processor and an endoscope connected to the endoscope processor and including an image pickup device that images the living tissue.

[0013] The endoscope system may further include an endoscope light source device configured to emit either first light in a first wavelength band or second light in a second wavelength band wider than the first wavelength band.

Advantages of the Invention

[0014] According to the above-described endoscope processor and endoscope system for an electronic endoscope, when acquiring a captured image of a living tissue and performing edge enhancement processing, it is possible to obtain a sufficient edge-enhanced image suitable for endoscope observation as compared with the prior art.

Brief Description of the Drawings

[0015] [Figure 1] It is a block diagram showing an example of the configuration of an electronic endoscope system according to an embodiment. [Figure 2] It is a block diagram showing an example of the configuration of the arithmetic unit shown in FIG. 1. [Figure 3] This is a conceptual block diagram representing the emphasis processing of one embodiment. [Figure 4] This figure shows an example of the flow of enhancement processing performed by an electronic endoscope processor in one embodiment. [Figure 5] This is a conceptual block diagram representing the emphasis processing of one embodiment. [Figure 6] This is a conceptual block diagram representing the emphasis processing of one embodiment. [Modes for carrying out the invention]

[0016] The processor of the electronic endoscope system of this embodiment separates the RGB color space information of the image obtained by imaging biological tissue with this system into a color difference component and a luminance component (Y component). Conventionally, when performing edge enhancement, edge components were detected using a spatial filter such as a Laplacian filter on the luminance component and combined with the original luminance component. However, when this conventional edge enhancement method was applied to images obtained from biological tissue in a body cavity using an endoscope, sufficient edge enhancement was sometimes not achieved. In images observed by an endoscope, it is necessary to enhance areas with strong redness, such as blood vessels and lesions, but conventional edge enhancement methods could not sufficiently enhance areas with strong redness. Therefore, the inventors of this application focused on the fact that the reddish areas to be emphasized have a strong contrast with the G (Green) and B (Blue) components, and found that emphasizing primarily using the G and B components rather than the luminance components of the image yields an emphasis effect more suitable for endoscopic observation.

[0017] In one embodiment of the endoscopic system, a feature portion containing at least one of the G component and the B component, rather than the Y component, is extracted from the captured image, and edge components are extracted from the extracted feature portion. This edge component extraction method may use a Laplacian filter or other known filters. Then, the extracted edge components are weighted and added to the luminance component, and the information is converted into RGB color space information. The weighting of the edge components may be adjusted according to the type of disease being observed. In one embodiment of the endoscopic system, areas with a strong reddish tint are enhanced using edge components of the G component and the B component, which have strong contrast, so areas with a strong reddish tint, such as lesions, can be enhanced more than in conventional methods.

[0018] The electronic endoscope system of this embodiment will be described in detail below with reference to the drawings. Figure 1 is a block diagram showing an example of the configuration of the electronic endoscope system 1 of this embodiment. As shown in Figure 1, the electronic endoscope system 1 is a system specifically designed for medical use and comprises an electronic scope (endoscope) 100, a processor 200, and a monitor 300.

[0019] The processor 200 includes a system controller 21 and a timing controller 22. The system controller 21 executes various programs stored in the memory 23 and provides integrated control of the entire electronic endoscope system 1. The system controller 21 is also connected to the operation panel 24. The system controller 21 changes each operation of the electronic endoscope system 1 and the parameters for each operation in response to instructions from the operator input into the operation panel 24. The timing controller 22 outputs clock pulses to each circuit in the electronic endoscope system 1 to adjust the timing of the operation of each part.

[0020] The processor 200 is equipped with a light source device 201. The light source device 201 emits illumination light L for illuminating a subject such as biological tissue in a body cavity. The illumination light L includes white light, pseudo-white light, or special light. According to one embodiment, the light source device 201 preferably selects one of two modes: one in which it constantly emits white light or pseudo-white light as illumination light L, and another in which it alternately emits white light or pseudo-white light and special light as illumination light L, and emits white light, pseudo-white light, or special light based on the selected mode. White light is light having a flat spectral intensity distribution in the visible light band, while pseudo-white light is light whose spectral intensity distribution is not flat and is a mixture of light from multiple wavelength bands. Special light is light in a narrow wavelength band such as blue or green within the visible light band. Light in the blue or green wavelength band is used when highlighting and observing specific parts of biological tissue. The illumination light L emitted from the light source device 201 is focused by the focusing lens 25 onto the incident end face of the LCB (Light Carrying Bundle) 11 and then incident into the LCB 11.

[0021] Illumination light L, incident within the LCB11, propagates through the LCB11. The illumination light L that has propagated through the LCB11 is emitted from the exit end face of the LCB11 located at the tip of the electronic scope 100 and illuminates the subject via the light distribution lens 12. The reflected light from the subject illuminated by the illumination light L from the light distribution lens 12 forms an optical image on the light-receiving surface of the solid-state image sensor 14 via the objective lens 13.

[0022] The solid-state image sensor 14 is a single-chip color CCD (Charge Coupled Device) image sensor with a Bayer-type pixel arrangement. The solid-state image sensor 14 accumulates the optical image formed by each pixel on the light-receiving surface as an electric charge corresponding to the amount of light, and generates and outputs R (Red), G (Green), and B (Blue) image signals. The solid-state image sensor 14 is not limited to a CCD image sensor; it may be replaced with a CMOS (Complementary Metal Oxide Semiconductor) image sensor or other types of imaging devices. The solid-state image sensor 14 may also be equipped with a complementary color filter.

[0023] A driver signal processing circuit 15 is provided within the connection section of the electronic scope 100. The driver signal processing circuit 15 receives the image signal of the subject from the solid-state image sensor 14 at a predetermined frame period. The frame period is, for example, 1 / 30 of a second. The driver signal processing circuit 15 performs predetermined processing on the image signal input from the solid-state image sensor 14 and outputs it to the pre-signal processing circuit 26 of the processor 200.

[0024] The driver signal processing circuit 15 also accesses the memory 16 to read out unique information of the electronic scope 100. The unique information of the electronic scope 100 recorded in the memory 16 includes, for example, the number of pixels and sensitivity of the solid-state image sensor 14, the operable frame rate, and the model number. The driver signal processing circuit 15 outputs the unique information read from the memory 16 to the system controller 21. This unique information may include, for example, element-specific information such as the number of pixels and resolution of the solid-state image sensor 14, as well as information related to the optical system such as the angle of view, focal length, and depth of field.

[0025] The system controller 21 performs various calculations based on the unique information of the electronic scope 100 and generates control signals. Using the generated control signals, the system controller 21 controls the operation and timing of various circuits within the processor 200 so that processing appropriate for the electronic scope 100 connected to the processor 200 is performed.

[0026] The timing controller 22 supplies clock pulses to the driver signal processing circuit 15 according to the timing control by the system controller 21. The driver signal processing circuit 15 drives the solid-state image sensor 14 in accordance with the clock pulses supplied from the timing controller 22, at a timing synchronized with the frame rate of the video processed on the processor 200 side.

[0027] The pre-stage signal processing circuit 26 applies predetermined signal processing, such as demosaicing and matrix calculations, to the image signal input from the driver signal processing circuit 15 at one-frame intervals, and outputs it to the image memory 27.

[0028] The image memory 27 buffers the image signal input from the preceding signal processing circuit 26 and outputs it to the subsequent signal processing circuit 28 according to the timing control by the timing controller 22.

[0029] The subsequent signal processing circuit 28 processes the image signal input from the image memory 27 to generate screen data for monitor display, and converts the generated screen data for monitor display into a predetermined video format signal. The converted video format signal is output to the monitor 300. As a result, the image of the subject is displayed on the display screen of the monitor 300.

[0030] A calculation unit 29 is connected to the system controller 21. The calculation unit 29 is responsible for performing enhancement processing on captured images retrieved from the image memory 27, which stores images of biological tissue, via the system controller 21. Figure 2 is a block diagram showing an example of the configuration of the calculation unit 29. The calculation unit 29 comprises a Y / C separation unit 30, a feature component extraction unit 31, an edge component extraction unit 32, an addition unit 33, and a conversion unit 34. The arithmetic unit 29 may be a software module formed by the system controller 21 activating a program stored in memory 23, or it may be a hardware module composed of an FPGA (Field-Programmable Gate Array). Figure 3 shows the RGB color space information of the image of biological tissue acquired from the image memory 27 ("Input Image IM"). IN "The enhancement process is applied to the output image IM. OUT This shows a conceptual block diagram of the process to obtain [the result].

[0031] Referring to FIG. 2, the Y / C separation unit 30 separates the input image IM obtained from the front-stage signal processing circuit 26 IN into color difference components (Cr component and Cb component) and a luminance component (Y component). The input image IM IN is, for example, an image signal buffered in the image memory 27. In other embodiments, the RGB color space may be converted into another color space other than the YCrCb space.

[0032] The feature component extraction unit 31 extracts a feature component including at least one of the G component and the B component from the input image IM IN The feature component is a signal component for enhancement processing that is the target of edge component extraction among the input image IM IN In order to more effectively enhance the reddish parts such as blood vessels and lesions in the captured image, the feature component includes at least one of the G component and the B component with strong contrast with respect to the reddish parts among the input image IM IN That is, at least one of the G component and the B component with strong contrast is included.

[0033] The edge component extraction unit 32 extracts an edge component from the feature component extracted by the feature component extraction unit 31. For the process of extracting the edge component, a known spatial filter such as a Laplacian filter or a Sobel filter can be adopted.

[0034] The addition unit 33 performs a predetermined weighting on the edge component extracted by the edge component extraction unit 32 and adds it to the luminance component Y obtained from the Y / C separation unit 30. Thereby, the luminance component Y separated from the input image IM IN is corrected using the edge components of the G component and the B component. The setting of the weighting can be adjusted according to the type of disease of the observation target. Preferably, the setting of the weighting can be changed by an operation input from the operation panel 24.

[0035] The conversion unit 34 converts the color difference component obtained by the Y / C separation unit 30 and the luminance component obtained by the addition unit 33 into information in the RGB color space. Thereby, the input image IM INEdge enhancement applied to the output image IM OUT The output image IM is obtained. OUT For example, the data is output to the image memory 27 for processing in the subsequent signal processing circuit 28.

[0036] In the biological tissues within the body cavities of the patient being studied, the red (R) component of the image color is dominant over the other components (G and B) due to the influence of hemoglobin pigments, etc. When the degree of lesion is low and the lesion is an inflamed area, the stronger the inflammation, the stronger the red (R) component becomes compared to the other colors (G and B). Therefore, in one embodiment of the endoscopic system, a feature portion containing at least one of the G and B components, rather than the Y component, is extracted from the captured image, and edge components are extracted from the extracted feature portion. The extracted edge components are weighted and added to the luminance component, and then converted into information in the RGB color space. In other words, in one embodiment of the endoscopic system, areas with a strong reddish tint are enhanced using edge components of the G and B components, which have strong contrast, making areas with a strong reddish tint, such as lesions, stand out more than in conventional methods.

[0037] Figure 4 shows an example of the flow of a collaborative processing operation performed by the processor 200 in one embodiment. The calculation unit 29, via the system controller 21, acquires a frame-by-frame captured image (image in RGB color space) that the preceding signal processing circuit 26 outputs to the image memory 27 (step S100), and then processes the acquired image into the input image IM. IN Then, each process from step S102 onward is performed. In other words, the Y / C separation unit 30 controls the input image IM IN The image is separated into color difference components (Cr component and Cb component) and luminance component (Y component) (step S102). The feature component extraction unit 31 extracts the input image IM IN A feature component containing at least one of the G component and the B component is extracted (step S104). The edge component extraction unit 32 applies a spatial filter, such as a Laplacian filter, to the feature component extracted by the feature component extraction unit 31 to extract edge components (step S106). Next, the addition unit 33 performs a weighted sum calculation by assigning predetermined weights to the edge components extracted by the edge component extraction unit 32 and adding them to the luminance component Y obtained from the Y / C separation unit 30 (step S108). The conversion unit 34 converts the color difference component obtained in step S102 and the luminance component obtained in step S108 into RGB color space information (step S110). As a result, the input image IM IN Edge enhancement applied to the output image IM OUT You can obtain this. The system controller 21 receives the output image IM. OUT The output is sent to the image memory 27. The subsequent signal processing circuit 28 receives the image IM from the image memory 27. OUT Obtain image IM OUT The signal is converted to a predetermined video format signal and output to the monitor 300. As a result, the image converted in step S110 is displayed (step S112).

[0038] In one embodiment, the feature components extracted by the feature component extraction unit 31 are the input image IM IN This information may involve assigning a positive weight to at least one of the G and B components. For example, the feature component may include an R component, but at least one of the G and B components may be given a stronger positive weight than the R component. This allows for emphasis on areas with strong red tones using the edge components of the G and B components, which have strong contrast.

[0039] In one embodiment, the feature component extraction unit 31 is the input image IM IN Multiple feature components may be extracted from the input image IM. In that case, the edge component extraction unit 32 extracts an edge component from each of the multiple feature components, and the addition unit 33 adds each extracted edge component to the luminance component by assigning a predetermined weight to it. When performing such processing, the input image IM IN Output image IM OUT Figure 5 shows a conceptual block diagram of the process for obtaining the desired result. By combining multiple feature components, it is possible to highlight and display only specific features.

[0040] In one embodiment, the input image IM IN Multiple feature components extracted from the input image IM IN The first feature portion consists of the R component, and the input image IM IN It includes a second feature portion consisting of the G component and the B component. The edge component extraction unit 32 extracts the R component edge component from the first feature portion and extracts the G component and the B component edge components from the second feature portion. In relation to this embodiment, Figure 6 shows the input image IM. IN Enhancement processing is applied to the output image IM OUT A conceptual block diagram of the process to obtain the result is shown. In Figure 6, the "R component edge" corresponds to the edge component of the R component extracted from the first feature part, and the "GB component edge" corresponds to the edge components of the G component and B component extracted from the second feature part.

[0041] Here, as shown in Figure 6, for example, the input image IM IN When blood vessels and folds are included, the R component edge will not include the reddish parts such as blood vessels, but will only include the edges of folds and shaded areas. On the other hand, the GB component edge will include the edges of the reddish parts such as blood vessels. Therefore, by adding a negative weight to the R component edge and a positive weight to the GB component edge and adding (combining) them with the luminance component, the output image IM is obtained. OUT This allows for the emphasis of areas with strong redness, such as blood vessels and redness, without emphasizing folds.

[0042] Although the electronic endoscope processor and electronic endoscope system of the present invention have been described in detail above, the electronic endoscope processor and electronic endoscope system of the present invention are not limited to the above embodiments, and various improvements and modifications may be made without departing from the spirit of the present invention. [Explanation of symbols]

[0043] 1. Electronic Endoscope System 11 LCB 12 Light distribution lenses 13 Objective lens 14 Solid-state image sensor 15. Driver signal processing circuit 16 memory 21 System Controller 22 Timing Controller 24 Control Panel 25 Focusing lens 26 Pre-stage signal processing circuit 27 Image memory 28. Subsequent signal processing circuit 29 Arithmetic section 30 Y / C separation section 31 Characteristic component extraction section 32 Edge component extraction section 33 Addition section 34 Conversion Unit 100 Electronic Scopes 200 processors 300 monitors

Claims

1. An electronic endoscope processor that acquires and enhances images of biological tissue, A separation unit separates the RGB color space information of an image of biological tissue into color difference components and luminance components. A feature component extraction unit extracts a plurality of feature components from the RGB color space information of the captured image, including a first feature portion consisting of the R component of the captured image and a second feature portion which is information to which a positive weight is given to at least one of the G component and B component of the captured image. An edge component extraction unit that extracts a first edge component from the first feature portion and a second edge component from the second feature portion, An adder that assigns a negative weight to the first edge component and a positive weight to the second edge component and adds them to the luminance component, The system includes a conversion unit that converts the color difference component and the luminance component obtained by the addition unit into information in the RGB color space. Processor for electronic endoscopes.

2. The endoscopic processor according to claim 1, An endoscope system comprising: an endoscope connected to the endoscope processor and equipped with an image sensor for imaging biological tissue.

3. The endoscope light source device further comprises a device configured to emit either a first light in a first wavelength band or a second light in a second wavelength band wider than the first wavelength band. The endoscopic system according to claim 2.

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