CN114827442B

CN114827442B - Method for generating image and electronic equipment

Info

Publication number: CN114827442B
Application number: CN202110129831.9A
Authority: CN
Inventors: 于頔; 郭宏伟
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2021-01-29
Filing date: 2021-01-29
Publication date: 2023-07-11
Anticipated expiration: 2041-01-29
Also published as: WO2022161011A1; CN114827442A

Abstract

The application relates to the field of terminal AI, in particular to the field of image generation, and provides a method and electronic equipment for generating an image, wherein the method comprises the following steps: acquiring n first images and n first spectrum data acquired by an image acquisition device; wherein one first spectrum data corresponds to one first image, the first spectrum data is lattice hyperspectral data or linear hyperspectral data, and n is a positive integer greater than or equal to 2; determining registration parameters required for image registration of the ith first image, and traversing 1 to n by i; processing the ith first spectrum data by using the registration parameter to obtain the ith second spectrum data, wherein the ith first spectrum data is the spectrum data corresponding to the ith first image, and i traverses 1 to n; and generating a second image according to the obtained n second spectrum data, wherein the second image is an area array hyperspectral image. The method does not need to assist in generating the area array hyperspectral image by means of complex mechanical equipment, and has strong applicability.

Description

Method for generating image and electronic equipment

Technical Field

The present application relates to the field of terminal artificial intelligence (artificial intelligence, AI), in particular to the field of image generation, and in particular to a method and an electronic device for generating an image.

Background

The hyperspectral imaging technology is a branch technology which is rapidly developed in the remote sensing technology, and through hyperspectral sensors mounted on different space platforms, a target area is imaged at the same time in tens to hundreds of continuous and subdivided spectral bands in the ultraviolet, visible, near infrared and mid infrared regions of the electromagnetic spectrum, so that not only can the spatial information of the target area be obtained, but also the spectral information of the target area can be obtained, and therefore, the hyperspectral imaging technology has great application value and wide development prospect in the field of image generation.

The current popular hyperspectral sensor is a single-point or linear array hyperspectral sensor, a target can be scanned to obtain single-point or linear array hyperspectral data, and then an area array hyperspectral image is generated through the single-point or linear array hyperspectral data. The traditional technology adopts a push-broom imaging method, a complex mechanical device is used for scanning a target at a fixed push-broom speed, and then single-point or linear array hyperspectral data obtained by scanning are processed based on the push-broom speed to obtain an area array hyperspectral image.

However, it is difficult for the electronic apparatus of the mobile terminal type to incorporate the above-described complicated mechanical device, so that the applicability of the push-broom type imaging method in the conventional art is low.

Disclosure of Invention

The method and the electronic device for generating the image are free from being assisted by complex mechanical equipment, have high applicability and greatly improve the capability of the electronic device for generating the area array hyperspectral image.

In a first aspect, the present application provides a method of generating an image, for use in an electronic device comprising an image acquisition apparatus, the method comprising: acquiring n first images and n first spectrum data acquired by an image acquisition device; wherein one first spectrum data corresponds to one first image, the first spectrum data is lattice hyperspectral data or linear hyperspectral data, and n is a positive integer greater than or equal to 2; determining registration parameters required by the ith first image for image registration, and traversing 1 to n by i; processing the ith first spectrum data by using the registration parameters to obtain the ith second spectrum data; wherein the ith first spectral data is spectral data corresponding to the ith first image, i traversing 1 through n; and generating a second image according to the obtained n second spectrum data, wherein the second image is an area array hyperspectral image.

The image acquisition device can comprise a visible light camera and a hyperspectral sensor, the first image can be a visible light image, and the second spectrum data are obtained by carrying out transformation processing on the first spectrum data, such as coordinate transformation and the like.

In the implementation manner, the electronic equipment adopts registration parameters required during visible light image registration, performs transformation processing on the point array hyperspectral data or the linear array hyperspectral data, and finally is spliced into the area array hyperspectral image. The method does not need to assist in generating the area array hyperspectral image by means of complex mechanical equipment, has high applicability and greatly improves the capability of generating the area array hyperspectral image by the electronic equipment.

With reference to the first aspect, in some implementations of the first aspect, determining a registration parameter required for image registration of the ith first image specifically includes: selecting a j-th first image from the n first images as a reference image of the i-th first image, wherein the j-th first image is different from the i-th first image; extracting features of the j-th first image to obtain a first feature point, extracting features of the i-th first image to obtain a second feature point, and determining a matched feature point pair according to the first feature point and the second feature point; and determining registration parameters of the ith first image according to the coordinate information of the matched characteristic point pairs.

In the implementation manner, the electronic device performs feature extraction on the reference image and the ith first image to obtain the matched feature point pair, so that the registration parameter of the ith first image is determined, data preparation is provided for subsequent transformation processing of the point array hyperspectral data or the linear array hyperspectral data, and further, the assistance is not needed by means of complex mechanical equipment, so that the applicability is high.

With reference to the first aspect, in some implementations of the first aspect, the jth first image is a previous frame image adjacent to the ith first image, and the method further includes: performing image registration on the ith first image by using registration parameters of the ith first image to obtain a registered ith first image; and taking the i first image after registration as a reference image of the i+1st first image.

In the implementation manner, the image adjacent to the ith first image is selected as the reference image, and the ith first image after image registration is continuously used as the reference image of the (i+1) th first image, so that the n first images are registered to the same spatial domain, the accuracy of image registration is further improved, more accurate data preparation is provided for the subsequent transformation processing of the point array hyperspectral data or the linear array hyperspectral data, and the accuracy of the obtained area array hyperspectral image is further improved.

With reference to the first aspect, in some implementations of the first aspect, the image capturing device includes a TOF lens, and determines a matched pair of feature points according to the first feature point and the second feature point, including: acquiring first three-dimensional coordinate information of a first feature point and second three-dimensional coordinate information of a second feature point; the first three-dimensional coordinate information and the second three-dimensional coordinate information are obtained by calculation according to the acquired data of the TOF lens; and matching the first characteristic points with the second characteristic points according to the first three-dimensional coordinate information and the second three-dimensional coordinate information, and determining matched characteristic point pairs.

In the implementation manner, the electronic equipment adopts the three-dimensional coordinate information of the characteristic point pairs to match, so that the accuracy of the matched characteristic point pairs can be improved, and the accuracy of registration parameters is further improved.

With reference to the first aspect, in some implementations of the first aspect, an inertial sensor is configured in the electronic device, and before feature extraction is performed on the jth first image to obtain a first feature point, and feature extraction is performed on the ith first image to obtain a second feature point, the method further includes: according to sensor data acquired by the inertial sensor when the image acquisition device acquires the jth first image, performing image optimization on the jth first image to obtain an optimized jth first image; and (3) performing image optimization on the ith first image according to the sensor data acquired by the inertial sensor when the ith first image is acquired by the image acquisition device, so as to obtain the optimized ith first image.

In the implementation manner, the electronic device performs the process of performing image optimization on the first image and then performing feature extraction, so that the accuracy of the obtained feature points can be improved, the accuracy of the obtained registration parameters can be further improved, the point array hyperspectral data or the linear array hyperspectral data can be subjected to transformation processing on the basis, and the accuracy of the obtained area array hyperspectral image can be improved.

With reference to the first aspect, in some implementations of the first aspect, the method further includes: based on the second image, defogging the target image by adopting a preset algorithm to obtain a defogged target image; the target image is the ith first image or is a spliced image generated by carrying out image registration on n first images.

In the implementation manner, on the basis of the area array hyperspectral image, the defogging treatment is carried out on the foggy image based on the hyperspectral image and the visible light image fusion method, so that the definition of the visible light image can be improved, and the image quality is further improved.

In a second aspect, the present application provides an apparatus, which is included in an electronic device, and which has a function of implementing the electronic device behavior in the first aspect and possible implementations of the first aspect. The functions may be realized by hardware, or may be realized by hardware executing corresponding software. The hardware or software includes one or more modules or units corresponding to the functions described above. Such as processing modules or units, etc.

In a third aspect, the present application provides an electronic device, the electronic device comprising: the system comprises an image acquisition device, one or more processors, one or more memories and a module provided with a plurality of application programs; the memory stores one or more programs that, when executed by the processor, cause the electronic device to perform any of the methods of the first aspect.

In a fourth aspect, the present application provides a chip comprising a processor. The processor is configured to read and execute a computer program stored in the memory to perform the method of the first aspect and any possible implementation thereof.

Optionally, the chip further comprises a memory, and the memory is connected with the processor through a circuit or a wire.

Further optionally, the chip further comprises a communication interface.

In a fifth aspect, the present application provides a computer readable storage medium, in which a computer program is stored, which when executed by a processor causes the processor to perform any one of the methods of the first aspect.

In a sixth aspect, the present application provides a computer program product comprising: computer program code which, when run on an electronic device, causes the electronic device to perform any one of the methods of the solutions of the first aspect.

Drawings

Fig. 1 is a schematic structural diagram of an example of an electronic device according to an embodiment of the present application;

FIG. 2 is a block diagram of a software architecture of an electronic device provided in an embodiment of the present application;

FIG. 3 is a schematic diagram of a system architecture of an example of a method for generating an image according to an embodiment of the present disclosure;

FIG. 4 is a flowchart illustrating an example of a method for generating an image according to an embodiment of the present disclosure;

fig. 5 is a schematic diagram of an example of a shooting interface of an electronic device according to an embodiment of the present application;

FIG. 6 is a flow chart of another example method for generating an image provided by an embodiment of the present application;

fig. 7 is a flowchart of another method for generating an image according to an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application. Wherein, in the description of the embodiments of the present application, "/" means or is meant unless otherwise indicated, for example, a/B may represent a or B; "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In addition, in the description of the embodiments of the present application, "plurality" means two or more than two.

The terms "first," "second," "third," and the like, are used below for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first", "a second", or a third "may explicitly or implicitly include one or more such feature.

In general, in order to further analyze spatial information of some target objects, two-dimensional geometric spatial information and one-dimensional spectral information of the target objects can be detected by means of hyperspectral imaging technology, so as to obtain continuous and narrow-band image data with high spectral resolution. Currently, the hyperspectral sensor is a single-point type or linear array type sensor which is mostly used in the market under the influence of the volume and cost of the hyperspectral sensor, and when an area array hyperspectral image is generated based on single-point type or linear array hyperspectral data, an external mechanical device is required to be combined, a target object is scanned at a fixed push-broom speed, and then the single-point type or linear array hyperspectral data is converted and spliced based on the push-broom speed to generate the area array hyperspectral image. However, for a handheld device or a mobile device, it is difficult to build in an external mechanical device with large size, high cost and low portability, and the above method is not applicable to the handheld device or the mobile device.

In view of this, the embodiments of the present application provide a method for generating an image, which may be applied to an electronic device including an image capturing device, such as a mobile phone, a tablet computer, a wearable device, a vehicle-mounted device, an augmented reality (augmented reality, AR)/Virtual Reality (VR) device, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (personal digital assistant, PDA), and the like. The image acquisition device can comprise a camera, a hyperspectral sensor and the like. The electronic equipment utilizes the image registration information of the visible light image acquired by the image acquisition device to generate an area array hyperspectral image by combining the dot matrix or linear array hyperspectral data acquired by the hyperspectral sensor. The method for generating the image can generate the area array hyperspectral image without external mechanical equipment, and has strong applicability. It should be clear that the embodiments of the present application do not set any limit to the specific type of electronic device.

Fig. 1 is a schematic structural diagram of an electronic device 100 according to an embodiment of the present application. The electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (universal serial bus, USB) interface 130, a charge management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, a sensor module 180, keys 190, a motor 191, an indicator 192, a camera 193, a display 194, and a subscriber identity module (subscriber identification module, SIM) card interface 195, etc. The sensor module 180 may include a pressure sensor 180A, a gyro sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, and the like.

It is to be understood that the structure illustrated in the embodiments of the present application does not constitute a specific limitation on the electronic device 100. In other embodiments of the present application, electronic device 100 may include more or fewer components than shown, or certain components may be combined, or certain components may be split, or different arrangements of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

The processor 110 may include one or more processing units, such as: the processor 110 may include an application processor (application processor, AP), a modem processor, a graphics processor (graphics processing unit, GPU), an image signal processor (image signal processor, ISP), a controller, a memory, a video codec, a digital signal processor (digital signal processor, DSP), a baseband processor, and/or a neural network processor (neural-network processing unit, NPU), etc. Wherein the different processing units may be separate devices or may be integrated in one or more processors.

The controller may be a neural hub and a command center of the electronic device 100, among others. The controller can generate operation control signals according to the instruction operation codes and the time sequence signals to finish the control of instruction fetching and instruction execution.

A memory may also be provided in the processor 110 for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. The memory may hold instructions or data that the processor 110 has just used or recycled. If the processor 110 needs to reuse the instruction or data, it may be called directly from memory. Repeated accesses are avoided and the latency of the processor 110 is reduced, thereby improving the efficiency of the system.

In some embodiments, the processor 110 may include one or more interfaces. The interfaces may include an integrated circuit (inter-integrated circuit, I2C) interface, an integrated circuit built-in audio (inter-integrated circuit sound, I2S) interface, a pulse code modulation (pulse code modulation, PCM) interface, a universal asynchronous receiver transmitter (universal asynchronous receiver/transmitter, UART) interface, a mobile industry processor interface (mobile industry processor interface, MIPI), a general-purpose input/output (GPIO) interface, a subscriber identity module (subscriber identity module, SIM) interface, and/or a universal serial bus (universal serial bus, USB) interface, among others.

The I2C interface is a bi-directional synchronous serial bus comprising a serial data line (SDA) and a serial clock line (derail clock line, SCL). In some embodiments, the processor 110 may contain multiple sets of I2C buses.

The I2S interface may be used for audio communication. In some embodiments, the processor 110 may contain multiple sets of I2S buses. The processor 110 may be coupled to the audio module 170 via an I2S bus to enable communication between the processor 110 and the audio module 170.

PCM interfaces may also be used for audio communication to sample, quantize and encode analog signals. In some embodiments, the audio module 170 and the wireless communication module 160 may be coupled through a PCM bus interface.

The UART interface is a universal serial data bus for asynchronous communications. The bus may be a bi-directional communication bus. It converts the data to be transmitted between serial communication and parallel communication. In some embodiments, a UART interface is typically used to connect the processor 110 with the wireless communication module 160.

The MIPI interface may be used to connect the processor 110 to peripheral devices such as a display 194, a camera 193, and the like. The MIPI interfaces include camera serial interfaces (camera serial interface, CSI), display serial interfaces (display serial interface, DSI), and the like. In some embodiments, processor 110 and camera 193 communicate through a CSI interface to implement the photographing functions of electronic device 100. The processor 110 and the display 194 communicate via a DSI interface to implement the display functionality of the electronic device 100.

The GPIO interface may be configured by software. The GPIO interface may be configured as a control signal or as a data signal. In some embodiments, a GPIO interface may be used to connect the processor 110 with the camera 193, the display 194, the wireless communication module 160, the audio module 170, the sensor module 180, and the like. The GPIO interface may also be configured as an I2C interface, an I2S interface, a UART interface, an MIPI interface, etc.

The USB interface 130 is an interface conforming to the USB standard specification, and may specifically be a Mini USB interface, a Micro USB interface, a USB Type C interface, or the like. The USB interface 130 may be used to connect a charger to charge the electronic device 100, and may also be used to transfer data between the electronic device 100 and a peripheral device. And can also be used for connecting with a headset, and playing audio through the headset. The interface may also be used to connect other electronic devices, such as AR devices, etc.

It should be understood that the interfacing relationship between the modules illustrated in the embodiments of the present application is only illustrative, and does not limit the structure of the electronic device 100. In other embodiments of the present application, the electronic device 100 may also use different interfacing manners, or a combination of multiple interfacing manners in the foregoing embodiments.

The charge management module 140 is configured to receive a charge input from a charger. The charger can be a wireless charger or a wired charger. In some wired charging embodiments, the charge management module 140 may receive a charging input of a wired charger through the USB interface 130. In some wireless charging embodiments, the charge management module 140 may receive wireless charging input through a wireless charging coil of the electronic device 100. The charging management module 140 may also supply power to the electronic device through the power management module 141 while charging the battery 142.

The power management module 141 is used for connecting the battery 142, and the charge management module 140 and the processor 110. The power management module 141 receives input from the battery 142 and/or the charge management module 140 and provides power to the processor 110, the internal memory 121, the external memory, the display 194, the camera 193, the wireless communication module 160, and the like. The power management module 141 may also be configured to monitor battery capacity, battery cycle number, battery health (leakage, impedance) and other parameters. In other embodiments, the power management module 141 may also be provided in the processor 110. In other embodiments, the power management module 141 and the charge management module 140 may be disposed in the same device.

The wireless communication function of the electronic device 100 may be implemented by the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, a modem processor, a baseband processor, and the like.

The antennas 1 and 2 are used for transmitting and receiving electromagnetic wave signals. The structures of the antennas 1 and 2 in fig. 1 are only one example. The mobile communication module 150 may provide a solution for wireless communication including 2G/3G/4G/5G, etc., applied to the electronic device 100. The mobile communication module 150 may include at least one filter, switch, power amplifier, low noise amplifier (low noise amplifier, LNA), etc. The mobile communication module 150 may receive electromagnetic waves from the antenna 1, perform processes such as filtering, amplifying, and the like on the received electromagnetic waves, and transmit the processed electromagnetic waves to the modem processor for demodulation. The mobile communication module 150 can amplify the signal modulated by the modem processor, and convert the signal into electromagnetic waves through the antenna 1 to radiate.

The modem processor may include a modulator and a demodulator. The modulator is used for modulating the low-frequency baseband signal to be transmitted into a medium-high frequency signal. The demodulator is used for demodulating the received electromagnetic wave signal into a low-frequency baseband signal. The demodulator then transmits the demodulated low frequency baseband signal to the baseband processor for processing. The low frequency baseband signal is processed by the baseband processor and then transferred to the application processor. The application processor outputs sound signals through an audio device (not limited to the speaker 170A, the receiver 170B, etc.), or displays images or video through the display screen 194. In some embodiments, the modem processor may be a stand-alone device. In other embodiments, the modem processor may be provided in the same device as the mobile communication module 150 or other functional module, independent of the processor 110.

The wireless communication module 160 may provide solutions for wireless communication including wireless local area network (wireless local area networks, WLAN) (e.g., wireless fidelity (wireless fidelity, wi-Fi) network), bluetooth (BT), global navigation satellite system (global navigation satellite system, GNSS), frequency modulation (frequency modulation, FM), near field wireless communication technology (near field communication, NFC), infrared technology (IR), etc., as applied to the electronic device 100. The wireless communication module 160 may be one or more devices that integrate at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via the antenna 2, modulates the electromagnetic wave signals, filters the electromagnetic wave signals, and transmits the processed signals to the processor 110. The wireless communication module 160 may also receive a signal to be transmitted from the processor 110, frequency modulate it, amplify it, and convert it to electromagnetic waves for radiation via the antenna 2.

The electronic device 100 implements display functions through a GPU, a display screen 194, an application processor, and the like. The GPU is a microprocessor for image processing, and is connected to the display 194 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. Processor 110 may include one or more GPUs that execute program instructions to generate or change display information.

The display screen 194 is used to display images, videos, and the like. The display 194 includes a display panel. The display panel may employ a liquid crystal display (liquid crystal display, LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode (AMOLED) or an active-matrix organic light-emitting diode (matrix organic light emitting diode), a flexible light-emitting diode (flex), a mini, a Micro led, a Micro-OLED, a quantum dot light-emitting diode (quantum dot light emitting diodes, QLED), or the like. In some embodiments, the electronic device 100 may include 1 or N display screens 194, N being a positive integer greater than 1.

The electronic device 100 may implement photographing functions through an ISP, a camera 193, a video codec, a GPU, a display screen 194, an application processor, and the like.

The ISP is used to process data fed back by the camera 193. For example, when photographing, the shutter is opened, light is transmitted to the camera photosensitive element through the lens, the optical signal is converted into an electrical signal, and the camera photosensitive element transmits the electrical signal to the ISP for processing, so that the electrical signal is converted into an image visible to naked eyes. ISP can also optimize the noise, brightness and skin color of the image. The ISP can also optimize parameters such as exposure, color temperature and the like of a shooting scene. In some embodiments, the ISP may be provided in the camera 193.

The camera 193 is used to capture still images or video. The object generates an optical image through the lens and projects the optical image onto the photosensitive element. The photosensitive element may be a charge coupled device (charge coupled device, CCD) or a Complementary Metal Oxide Semiconductor (CMOS) phototransistor. The photosensitive element converts the optical signal into an electrical signal, which is then transferred to the ISP to be converted into a digital image signal. The ISP outputs the digital image signal to the DSP for processing. The DSP converts the digital image signal into an image signal in a standard RGB, YUV, or the like format. In some embodiments, electronic device 100 may include 1 or N cameras 193, N being a positive integer greater than 1. In some embodiments, camera 193 may include a visible light camera for capturing visible light images. In some embodiments, camera 193 may also include a time of flight (TOF) lens. Where TOF is a measurement of the time it takes an object, particle or wave (e.g., acoustic wave, electromagnetic wave, etc.) to travel a distance in a medium. The TOF lens can emit waves and receive the waves reflected by the shot object after the waves meet the shot object. The electronic device may thus obtain the time difference of the TOF lens from transmitting the wave to receiving the reflected wave and/or the phase difference between the wave transmitted by the TOF lens and the received reflected wave. And the electronic equipment calculates the distance between the electronic equipment and the shot object according to the time difference and/or the phase difference to form a group of distance depth data, so as to obtain a 3D model or a 3D image containing the shot object depth information. Alternatively, the waves may be infrared light, laser pulses, ultrasonic waves, etc.

The digital signal processor is used for processing digital signals, and can process other digital signals besides digital image signals. For example, when the electronic device 100 selects a frequency bin, the digital signal processor is used to fourier transform the frequency bin energy, or the like.

Video codecs are used to compress or decompress digital video. The electronic device 100 may support one or more video codecs. In this way, the electronic device 100 may play or record video in a variety of encoding formats, such as: dynamic picture experts group (moving picture experts group, MPEG) 1, MPEG2, MPEG3, MPEG4, etc.

The NPU is a neural-network (NN) computing processor, and can rapidly process input information by referencing a biological neural network structure, for example, referencing a transmission mode between human brain neurons, and can also continuously perform self-learning. Applications such as intelligent awareness of the electronic device 100 may be implemented through the NPU, for example: image recognition, face recognition, speech recognition, text understanding, etc.

The external memory interface 120 may be used to connect an external memory card, such as a Micro SD card, to enable expansion of the memory capabilities of the electronic device 100. The external memory card communicates with the processor 110 through an external memory interface 120 to implement data storage functions. For example, files such as music, video, etc. are stored in an external memory card.

The internal memory 121 may be used to store computer-executable program code that includes instructions. The processor 110 executes various functional applications of the electronic device 100 and data processing by executing instructions stored in the internal memory 121. The internal memory 121 may include a storage program area and a storage data area. The storage program area may store an application program (such as a sound playing function, an image playing function, etc.) required for at least one function of the operating system, etc. The storage data area may store data created during use of the electronic device 100 (e.g., audio data, phonebook, etc.), and so on. In addition, the internal memory 121 may include a high-speed random access memory, and may further include a nonvolatile memory such as at least one magnetic disk storage device, a flash memory device, a universal flash memory (universal flash storage, UFS), and the like.

The electronic device 100 may implement audio functions through an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, an application processor, and the like. Such as music playing, recording, etc.

The pressure sensor 180A is used to sense a pressure signal, and may convert the pressure signal into an electrical signal. In some embodiments, the pressure sensor 180A may be disposed on the display screen 194. The pressure sensor 180A is of various types, such as a resistive pressure sensor, an inductive pressure sensor, a capacitive pressure sensor, and the like. The capacitive pressure sensor may be a capacitive pressure sensor comprising at least two parallel plates with conductive material. The capacitance between the electrodes changes when a force is applied to the pressure sensor 180A. The electronic device 100 determines the strength of the pressure from the change in capacitance. When a touch operation is applied to the display screen 194, the electronic apparatus 100 detects the touch operation intensity according to the pressure sensor 180A. The electronic device 100 may also calculate the location of the touch based on the detection signal of the pressure sensor 180A. In some embodiments, touch operations that act on the same touch location, but at different touch operation strengths, may correspond to different operation instructions. For example: and executing an instruction for checking the short message when the touch operation with the touch operation intensity smaller than the first pressure threshold acts on the short message application icon. And executing an instruction for newly creating the short message when the touch operation with the touch operation intensity being greater than or equal to the first pressure threshold acts on the short message application icon.

The gyro sensor 180B may be used to determine a motion gesture of the electronic device 100. In some embodiments, the angular velocity of electronic device 100 about three axes (i.e., x, y, and z axes) may be determined by gyro sensor 180B. The gyro sensor 180B may be used for photographing anti-shake. For example, when the shutter is pressed, the gyro sensor 180B detects the shake angle of the electronic device 100, calculates the distance to be compensated by the lens module according to the angle, and makes the lens counteract the shake of the electronic device 100 through the reverse motion, so as to realize anti-shake. The gyro sensor 180B may also be used for navigating, somatosensory game scenes.

The air pressure sensor 180C is used to measure air pressure. In some embodiments, electronic device 100 calculates altitude from barometric pressure values measured by barometric pressure sensor 180C, aiding in positioning and navigation.

The magnetic sensor 180D includes a hall sensor. The electronic device 100 may detect the opening and closing of the flip cover using the magnetic sensor 180D. In some embodiments, when the electronic device 100 is a flip machine, the electronic device 100 may detect the opening and closing of the flip according to the magnetic sensor 180D. And then according to the detected opening and closing state of the leather sheath or the opening and closing state of the flip, the characteristics of automatic unlocking of the flip and the like are set.

The acceleration sensor 180E may detect the magnitude of acceleration of the electronic device 100 in various directions (typically three axes). The magnitude and direction of gravity may be detected when the electronic device 100 is stationary. The electronic equipment gesture recognition method can also be used for recognizing the gesture of the electronic equipment, and is applied to horizontal and vertical screen switching, pedometers and other applications.

A distance sensor 180F for measuring a distance. The electronic device 100 may measure the distance by infrared or laser. In some embodiments, the electronic device 100 may range using the distance sensor 180F to achieve quick focus.

The proximity light sensor 180G may include, for example, a Light Emitting Diode (LED) and a light detector, such as a photodiode. The light emitting diode may be an infrared light emitting diode. The electronic device 100 emits infrared light outward through the light emitting diode. The electronic device 100 detects infrared reflected light from nearby objects using a photodiode. When sufficient reflected light is detected, it may be determined that there is an object in the vicinity of the electronic device 100. When insufficient reflected light is detected, the electronic device 100 may determine that there is no object in the vicinity of the electronic device 100. The electronic device 100 can detect that the user holds the electronic device 100 close to the ear by using the proximity light sensor 180G, so as to automatically extinguish the screen for the purpose of saving power. The proximity light sensor 180G may also be used in holster mode, pocket mode to automatically unlock and lock the screen.

The ambient light sensor 180L is used to sense ambient light level. The electronic device 100 may adaptively adjust the brightness of the display 194 based on the perceived ambient light level. The ambient light sensor 180L may also be used to automatically adjust white balance when taking a photograph. Ambient light sensor 180L may also cooperate with proximity light sensor 180G to detect whether electronic device 100 is in a pocket to prevent false touches.

The fingerprint sensor 180H is used to collect a fingerprint. The electronic device 100 may utilize the collected fingerprint feature to unlock the fingerprint, access the application lock, photograph the fingerprint, answer the incoming call, etc.

The temperature sensor 180J is for detecting temperature. In some embodiments, the electronic device 100 performs a temperature processing strategy using the temperature detected by the temperature sensor 180J.

The touch sensor 180K, also referred to as a "touch panel". The touch sensor 180K may be disposed on the display screen 194, and the touch sensor 180K and the display screen 194 form a touch screen, which is also called a "touch screen". The touch sensor 180K is for detecting a touch operation acting thereon or thereabout. The touch sensor may communicate the detected touch operation to the application processor to determine the touch event type. Visual output related to touch operations may be provided through the display 194. In other embodiments, the touch sensor 180K may also be disposed on the surface of the electronic device 100 at a different location than the display 194.

The bone conduction sensor 180M may acquire a vibration signal. In some embodiments, bone conduction sensor 180M may acquire a vibration signal of a human vocal tract vibrating bone pieces. The bone conduction sensor 180M may also contact the pulse of the human body to receive the blood pressure pulsation signal. In some embodiments, bone conduction sensor 180M may also be provided in a headset, in combination with an osteoinductive headset. The audio module 170 may parse out a voice signal based on the vibration signal of the vocal part vibration bone piece obtained by the bone conduction sensor 180M, and implement a voice function. The application processor can analyze heart rate information based on the blood pressure beat signals acquired by the bone conduction sensor 180M, so that a heart rate detection function is realized.

In some embodiments, the electronic device 100 further includes a hyperspectral sensor, which may be a lattice sensor or a linear array sensor, which may collect lattice hyperspectral data, and a linear array sensor which may collect linear array hyperspectral data.

The keys 190 include a power-on key, a volume key, etc. The keys 190 may be mechanical keys. Or may be a touch key. The electronic device 100 may receive key inputs, generating key signal inputs related to user settings and function controls of the electronic device 100.

The motor 191 may generate a vibration cue. The motor 191 may be used for incoming call vibration alerting as well as for touch vibration feedback. For example, touch operations acting on different applications (e.g., photographing, audio playing, etc.) may correspond to different vibration feedback effects. The motor 191 may also correspond to different vibration feedback effects by touching different areas of the display screen 194. Different application scenarios (such as time reminding, receiving information, alarm clock, game, etc.) can also correspond to different vibration feedback effects. The touch vibration feedback effect may also support customization.

The indicator 192 may be an indicator light, may be used to indicate a state of charge, a change in charge, a message indicating a missed call, a notification, etc.

The SIM card interface 195 is used to connect a SIM card. The SIM card may be inserted into the SIM card interface 195, or removed from the SIM card interface 195 to enable contact and separation with the electronic device 100. The electronic device 100 may support 1 or N SIM card interfaces, N being a positive integer greater than 1.

The software system of the electronic device 100 may employ a layered architecture, an event driven architecture, a microkernel architecture, a microservice architecture, or a cloud architecture. In this embodiment, taking an Android system with a layered architecture as an example, a software structure of the electronic device 100 is illustrated.

Fig. 2 is a software configuration block diagram of the electronic device 100 according to the embodiment of the present application. The layered architecture divides the software into several layers, each with distinct roles and branches. The layers communicate with each other through a software interface. In some embodiments, the Android system is divided into four layers, from top to bottom, an application layer, an application framework layer, an Zhuoyun row (Android run) and system libraries, and a kernel layer, respectively. The application layer may include a series of application packages.

As shown in fig. 2, the application package may include applications for cameras, gallery, calendar, phone calls, maps, navigation, WLAN, bluetooth, music, video, short messages, etc.

The application framework layer provides an application programming interface (application programming interface, API) and programming framework for application programs of the application layer. The application framework layer includes a number of predefined functions.

As shown in FIG. 2, the application framework layer may include a window manager, a content provider, a view system, a telephony manager, a resource manager, a notification manager, and the like.

The window manager is used for managing window programs. The window manager can acquire the size of the display screen, judge whether a status bar exists, lock the screen, intercept the screen and the like.

The content provider is used to store and retrieve data and make such data accessible to applications. The data may include video, images, audio, calls made and received, browsing history and bookmarks, phonebooks, etc.

The view system includes visual controls, such as controls to display text, controls to display pictures, and the like. The view system may be used to build applications. The display interface may be composed of one or more views. For example, a display interface including a text message notification icon may include a view displaying text and a view displaying a picture.

The telephony manager is used to provide the communication functions of the electronic device 100. Such as the management of call status (including on, hung-up, etc.).

The resource manager provides various resources for the application program, such as localization strings, icons, pictures, layout files, video files, and the like.

The notification manager allows the application to display notification information in a status bar, can be used to communicate notification type messages, can automatically disappear after a short dwell, and does not require user interaction. Such as notification manager is used to inform that the download is complete, message alerts, etc. The notification manager may also be a notification in the form of a chart or scroll bar text that appears on the system top status bar, such as a notification of a background running application, or a notification that appears on the screen in the form of a dialog window. For example, a text message is prompted in a status bar, a prompt tone is emitted, the electronic device vibrates, and an indicator light blinks, etc.

Android runtimes include core libraries and virtual machines. Android run time is responsible for scheduling and management of the Android system.

The core library consists of two parts: one part is a function which needs to be called by java language, and the other part is a core library of android.

The application layer and the application framework layer run in a virtual machine. The virtual machine executes java files of the application program layer and the application program framework layer as binary files. The virtual machine is used for executing the functions of object life cycle management, stack management, thread management, security and exception management, garbage collection and the like.

The system library may include a plurality of functional modules. For example: surface manager (surface manager), media library (media library), three-dimensional graphics processing library (e.g., openGL ES), 2D graphics engine (e.g., SGL), etc.

The surface manager is used to manage the display subsystem and provides a fusion of 2D and 3D layers for multiple applications.

Media libraries support a variety of commonly used audio, video format playback and recording, still image files, and the like. The media library may support a variety of audio and video encoding formats, such as MPEG4, h.264, MP3, AAC, AMR, JPG, PNG, etc.

The three-dimensional graphic processing library is used for realizing three-dimensional graphic drawing, image rendering, synthesis, layer processing and the like.

The 2D graphics engine is a drawing engine for 2D drawing.

The kernel layer is a layer between hardware and software. The inner core layer at least comprises a display driver, a camera driver, an audio driver and a sensor driver.

For ease of understanding, the following embodiments of the present application will take an electronic device having a structure shown in fig. 1 and fig. 2 as an example, and the method for generating an image provided in the embodiments of the present application will be specifically described with reference to the accompanying drawings.

The method for generating the image provided in the embodiment of the present application may be applied to the system architecture shown in fig. 3, and first, an application scenario of the embodiment of the present application is described with reference to fig. 3.

When the user holds the electronic equipment to carry out shooting for a plurality of times towards the target area, the electronic equipment can acquire a plurality of visible light images and a plurality of hyperspectral data, and the hyperspectral data can be lattice hyperspectral data or linear hyperspectral data. For convenience of description, the linear array hyperspectral data will be described as an example.

After the electronic device acquires the plurality of visible light images, the plurality of visible light images can be subjected to image registration to obtain registration parameters during image registration. Taking two visible light images a and B as an example, as shown in fig. 3, the electronic device may first perform image preprocessing on the image a and the image B, and then extract feature points in the image a and feature points in the image B. And then the electronic equipment matches the characteristic points in the image A with the characteristic points in the image B to obtain characteristic point pairs. Finally, the electronic device may calculate, according to the feature point pairs, a registration parameter of the spatial coordinate transformation between the image a and the image B, as shown in fig. 3, where the registration parameter may be a spatial coordinate transformation matrix, abbreviated as a transformation matrix. Wherein the image preprocessing includes, but is not limited to, a process of correcting the image based on camera internal parameters and distortion parameters. The feature points of the image can be determined by extracting the features of the pixel points in the image, and the features of the pixel points can comprise point features, line features and surface features; the extraction algorithm of the point features may include, but is not limited to, scale-invariant feature transform (SIFT) algorithm, SURF (speeded up robust features) algorithm and ORB (oriented fast and rotated brief) algorithm, the extraction algorithm of the line features may include, but is not limited to, log algorithm and canny algorithm, and the extraction algorithm of the face features may include, but is not limited to, region segmentation algorithm. Algorithms for feature point matching include, but are not limited to, euclidean distance algorithms, nearest neighbor (KNN), hamming distance algorithms, and similarity metric algorithms. Algorithms for solving the transformation matrix include, but are not limited to, random sample consensus (random sample consensus, RANSAC) algorithm, RHO algorithm, least Median (LMEDS) algorithm, and least squares algorithm.

In the method for generating the image provided by the embodiment of the application, the electronic equipment utilizes the registration parameter to perform coordinate conversion on the linear array hyperspectral data, and performs splicing processing on the linear array hyperspectral data subjected to the coordinate conversion, so that the planar array hyperspectral image is obtained, and the technical effect that the planar array hyperspectral image can be generated without using external mechanical equipment is achieved.

In addition, the electronic device can also utilize the registration parameters to perform coordinate conversion on pixel point coordinates in the visible light images so as to obtain the visible light images after image registration, and splice the visible light images after image registration.

Further, the electronic device may further perform post-processing on the stitched visible light image based on the obtained area array hyperspectral image, such as image defogging (as shown in fig. 3), image enhancement, and the like.

Optionally, the process of defogging the spliced visible light image based on the planar array hyperspectral image may include the processes of fog concentration estimation, image partition, image fusion, image filtering, and the like, and the specific implementation process may be described in the following method embodiments.

Optionally, the electronic device may further utilize the acquired data of the TOF lens, the acquired data of the hardware sensor, and the output interaction prompt information, so as to improve the accuracy of the registration parameter, and further improve the accuracy of the obtained area array hyperspectral image. As described above, the electronic device can calculate the depth information of the subject through the process of transmitting the wave and receiving the reflected wave by the TOF lens; the collected data of the hardware sensor may include acceleration of the electronic device, etc.

The method for generating an image provided in the embodiment of the present application is specifically described below. Fig. 4 is a flowchart of an example of a method for generating an image according to an embodiment of the present application, where the method includes:

s101, acquiring n first images and n first spectrum data acquired by an image acquisition device; wherein one first spectrum data corresponds to one first image, the first spectrum data is lattice hyperspectral data or linear hyperspectral data, and n is a positive integer greater than or equal to 2.

In this embodiment, the image acquisition device includes the visible light camera and the hyperspectral sensor described in the embodiment of fig. 1, where the visible light camera may acquire a visible light image (i.e., the first image), and the hyperspectral sensor may acquire lattice hyperspectral data or linear hyperspectral data (i.e., the first spectral data). When the user holds the electronic equipment to carry out shooting towards the target area once, the electronic equipment can collect a visible light image and first spectrum data at the same time. Therefore, in the continuous shooting or panoramic shooting mode, the electronic device can acquire a plurality (such as n) of visible light images and a plurality of first spectrum data of different angles of the target area in the same scene.

The position of the target area in the visible light image can be fixed, and the focal length of the visible light camera is kept consistent with the focal length of the hyperspectral sensor in order to ensure that the conversion between the first spectrum data and the visible light image is relatively synchronous. The process of camera imaging is typically a process of converting the world coordinate system into the pixel coordinate system, i.e. world coordinate system (3 d) -camera coordinate system (3 d) -image plane coordinate system (2 d) -pixel coordinate system (2 d). After such a first-order conversion, the coordinates of the target region in space are converted into pixel coordinates in the image. Optionally, after obtaining the visible light image, the electronic device may further perform correction preprocessing on the visible light image based on the camera internal parameters and distortion parameters.

Optionally, in the panoramic shooting mode, in order to make the user keep the electronic device flat as much as possible to shoot n visible light images located on the same horizontal line, some prompt information may be displayed on a display screen of the electronic device. For example, as shown in fig. 5, the presentation information may be a horizontal center line displayed on the photographing interface, and the center line may be used to assist the user in moving the target area as much as possible based on the center line during photographing. Optionally, the prompt information may further include a rectangular frame, and a captured image frame may be displayed in the rectangular frame; the rectangular frame may be located at one side, the center or near the center area of the display interface before the electronic device starts shooting; as more and more image frames are taken by the electronic device, the sides of the rectangular frame in the direction of the center line may become longer gradually, or the rectangular frame may be moved gradually along the center line. Therefore, the prompt information can be used for controlling the deviation range between the visible light images to obtain n visible light images with higher quality. Optionally, the prompt information may be a vertical center line displayed on a photographing interface of the electronic device, or may be a horizontal center line and a vertical center line simultaneously displayed on a photographing interface of the electronic device, so as to further improve the quality of photographing the visible light image.

S102, determining registration parameters required by the ith first image for image registration, and traversing 1 to n.

Specifically, after acquiring n visible light images, the electronic device may determine a registration parameter required for image registration of each visible light image, and as described above, the registration parameter may be a transformation matrix. Based on the transformation matrix, coordinate transformation can be carried out on pixel point coordinates in the visible light image so as to finish image registration; in this embodiment, the coordinate transformation may be further performed on the first spectrum data based on the transformation matrix to obtain the second spectrum data.

In one possible implementation, for the ith visible light image, image registration may be performed using the ith-1 th visible light image as a reference image, and a registration parameter corresponding to the ith visible light image may be determined. For example, with the 1 st visible image as a reference image, registering the 2 nd visible image onto the spatial domain of the 1 st visible image; and registering the 3 rd visible light image to the space domain of the 2 nd visible light image by taking the 2 nd visible light image as a reference image, and the like to obtain registration parameters required by each visible light image during registration.

In another possible implementation, any one of the n visible light images may be used as a reference image for the remaining n-1 images, and the registration parameters corresponding to the remaining n-1 visible light images may be determined. For example, the 1 st visible light image is selected as the reference image, and all of the 2 nd to nth visible light images are registered to the spatial domain of the 1 st visible light image.

S103, processing the ith first spectrum data by using the registration parameters to obtain the ith second spectrum data; wherein the ith first spectral data is spectral data corresponding to the ith first image.

Because each first spectrum data corresponds to one visible light image, and the conversion between the first spectrum data and the visible light images is relatively synchronous, the electronic device can process the first spectrum data by adopting the registration parameter corresponding to the visible light image, namely, the registration parameter of the ith visible light image is adopted to process the first spectrum data corresponding to the ith visible light image, so as to obtain the second spectrum data. As an example and not by way of limitation, the registration parameter of the ith visible light image may be used to coordinate transform the first spectral data corresponding to the ith visible light image, so that the first spectral data are all located in the same reference coordinate system, and the second spectral data are obtained.

S104, generating a second image according to the obtained n second spectrum data, wherein the second image is an area array hyperspectral image.

Specifically, the above-mentioned corresponding second spectrum data is obtained for each first spectrum data, and there are n second spectrum data, where the n second spectrum data are still lattice hyperspectral data or linear hyperspectral data, and then the electronic device may splice the n second spectrum data to generate an area array hyperspectral image.

In the above embodiment, the electronic device performs transformation processing on the point array hyperspectral data or the linear array hyperspectral data by adopting registration parameters required during the registration of the visible light image, and finally splices the point array hyperspectral data or the linear array hyperspectral data into the area array hyperspectral image. The method can generate the area array hyperspectral image without assistance of complex mechanical equipment, has strong applicability and greatly improves the capability of the electronic equipment for generating the area array hyperspectral image.

In one embodiment, as shown in fig. 6, the process of determining the registration parameters required for the image registration for the i-th first image in S102 may include:

s201, selecting a j-th first image in the n first images as a reference image of the i-th first image, wherein the j-th first image is different from the i-th first image.

Specifically, the reference image of the ith visible light image (i.e., the jth visible light image) may be determined in the manner described in the above embodiments, for example, selecting the ith-1 th visible light image or any one of the remaining visible light images as the reference image of the ith visible light image. Further, the jth visible light image may be a previous frame image adjacent to the ith visible light image, i.e. j may be i-1, and then the electronic device performs image registration on the ith first image by using the registration parameter of the ith first image, so as to obtain a registered ith first image, and then the registered ith first image may be used as a reference image of the (i+1) th first image. For example, the 1 st visible light image is used as a reference image, the 2 nd visible light image is registered to the spatial domain of the 1 st visible light image, then the 2 nd visible light image after registration is used as the reference image, the 3 rd visible light image is registered to the spatial domain of the 1 st visible light image, then the 3 rd visible light image after registration is used as the reference image, and the 4 th visible light image is registered to the spatial domain of the 3 rd visible light image, and the like, so that n visible light images can be registered to the same spatial domain, and the accuracy of each visible light image in image registration is improved.

S202, performing feature extraction on the j-th first image to obtain a first feature point, performing feature extraction on the i-th first image to obtain a second feature point, and determining a matched feature point pair according to the first feature point and the second feature point.

S203, determining registration parameters of the ith first image according to the coordinate information of the matched feature point pairs.

Specifically, after determining the reference image (i.e., the jth visible light image) of the ith visible light image, the electronic device may perform feature extraction on the two visible light images respectively to determine a matched feature point pair, and determine the registration parameter of the ith visible light image according to the coordinate information of the feature point pair.

By way of example and not limitation, the process of determining registration parameters is described taking as an example the image registration of the 1 st visible light image a (reference image) and the 2 nd visible light image B: first, extracting the characteristics of each pixel point in the image A and the characteristics of each pixel point in the image B to determine the first image in the image AThe feature points and the second feature points in image B, optionally, the pixel point features may include point features, line features, and plane features. Then, feature point matching is performed based on the first feature point of the image a and the second feature point of the image B, and a matched feature point pair is determined. Finally, a transformation matrix between the image A and the image B is determined based on the coordinate information of the matched feature point pairs. For example, assume that (a, B) is a matched pair of feature points, where a is a feature point of image A and B is a feature point of image B, assuming that the coordinates of a are (x ₁ ，y ₁ ) B has the coordinates (x) ₂ ，y ₂ ) Then there is a matrix H such that (x ₁ ,y ₁ )＝H×(x ₂ ,y ₂ ) H is then the transformation matrix, i.e. the registration parameter, used when registering image B to image a. It should be noted that, regarding the extraction algorithm of each feature, the matching algorithm of the feature point pair, and the algorithm for solving the transformation matrix, reference may be made to the description in the embodiment of fig. 3, which is not repeated herein.

In the above embodiment, the electronic device performs feature extraction on the reference image and the ith visible light image to obtain the matched feature point pair, so as to determine the registration parameter of the ith visible light image, provide data preparation for the subsequent transformation processing of the point array hyperspectral data or the linear array hyperspectral data, and further, does not need to assist by means of complex mechanical equipment, so that the applicability is strong.

In addition, in order to improve the accuracy of the registration parameter determined in the foregoing embodiment, in one embodiment, the image capturing device further includes a TOF lens described in the foregoing embodiment of fig. 1, three-dimensional coordinate information of each pixel point in the visible light image may be calculated by using acquired data of the TOF lens, and accordingly, the electronic device may obtain the three-dimensional coordinate information of the first feature point and the coordinate information of the second feature point, and the determining, in the step S202, the matched feature point pair according to the first feature point and the second feature point may include: according to the three-dimensional coordinate information of the first feature point and the three-dimensional coordinate information of the second feature point, the Euclidean distance algorithm, the KNN algorithm, the Hamming distance algorithm or the similarity measurement algorithm in the embodiment are adopted to match the first feature point with the second feature point, and matched feature point pairs are determined, so that the accuracy of the matched feature point pairs is improved, and the accuracy of registration parameters is further improved.

For an actual application scenario, in the process of shooting by a user holding an electronic device, phenomena such as shadows may occur in a shot visible light image due to shake or other factors, so that the embodiment of the application may further optimize the acquired visible light image, and then execute the process of extracting features to obtain feature points in S202 after the optimization. Optionally, an inertial sensor, such as an accelerometer, a gyroscope, and other sensors, may be configured in the electronic device, where the inertial sensor may collect sensor data representing a motion state of the electronic device in real time, and when the image collecting device collects the ith visible light image, the inertial sensor may also collect sensor data at a corresponding time, and when the jth visible light image is collected, the inertial sensor may also collect sensor data at a corresponding time; then, the electronic equipment can perform image optimization on the jth visible light image according to the sensor data acquired by the inertial sensor when the jth visible light image is acquired by the image acquisition device, so as to obtain the optimized jth visible light image; and (3) performing image optimization on the ith visible light image according to the sensor data acquired by the inertial sensor when the ith visible light image is acquired by the image acquisition device, so as to obtain the optimized ith visible light image.

Specifically, description will be given of an example of image optimization of the i-th visible light image. The inertial sensor can acquire the triaxial angular velocity and triaxial acceleration of the electronic equipment. The electronic equipment can utilize a Kalman filtering method to filter the triaxial angular velocity and the triaxial acceleration, then use an Euler dynamics equation to convert the triaxial angular velocity into Euler angles, and use a uniform acceleration motion equation to convert the triaxial acceleration into triaxial displacement, so as to obtain a rotation matrix and a translation matrix. Then, the electronic device may calculate the background light flow of the ith visible light image according to the rotation matrix and the translation matrix, and perform robust estimation on the background light flow of the ith visible light image by using the RANSAC algorithm, so as to remove the motion light flow existing in the background light flow, and complete image optimization on the ith visible light image. The process of image optimization of the j-th visible light image by the electronic device is similar to the process of image optimization of the i-th visible light image, and will not be described herein.

In the above embodiment, the electronic device performs the process of performing the feature extraction after performing the image optimization on the visible light image, so that the accuracy of the feature points of the obtained image can be improved, the accuracy of the matched feature point pairs can be further improved, the accuracy of the obtained registration parameters can be further improved, and the accuracy of the obtained area array hyperspectral image can be improved by performing the transformation processing on the point array hyperspectral data or the line array hyperspectral data on the basis of the accuracy of the obtained registration parameters.

For another practical application scenario, if the external environment is poor when the image acquisition device acquires the visible light image, if there is foggy weather, the acquired visible light image is low in definition and poor in quality, and the display effect of the visible light image is affected, then the electronic device in this embodiment may further perform defogging processing or image enhancement processing on the visible light image based on the acquired second image, i.e., the area array hyperspectral image, so as to improve the definition of the visible light image, and further improve the image quality of the visible light image.

In one possible implementation manner, the electronic device may perform defogging processing on the ith visible light image by using a preset algorithm based on the second image, so as to obtain the defogged ith visible light image.

Specifically, the preset algorithm may be a visible light near infrared image fusion algorithm, the electronic device may extract luminance values of corresponding pixels from a blue light channel of the ith visible light image and the second image, determine fog concentration distribution according to a difference of the luminance values of the corresponding pixels, then fuse the luminance values of the corresponding pixels in the second image and the ith visible light image according to the fog concentration distribution, obtain defogging luminance values, and finally generate the ith visible light image after defogging according to each defogging luminance value and a corresponding color value in the ith visible light image. Optionally, the electronic device may further perform image filtering on the ith visible light image, so as to further improve the image quality of the visible light image.

In another possible implementation manner, the electronic device may further perform defogging processing on the target image by using a preset algorithm based on the second image, so as to obtain a defogged target image, where the target image is a stitched image generated by performing image registration on n visible light images.

Specifically, after the electronic device determines registration parameters required for image registration for n visible light images, coordinate transformation can be performed on pixel point coordinates of the ith visible light image based on the registration parameters of the ith visible light image to obtain the ith visible light image after registration, and then the n visible light images after image registration are subjected to image stitching to generate a stitched visible light image; for example stitching a plurality of partial visible light images into a panoramic visible light image. Then, the visible light near infrared image fusion algorithm in the embodiment is adopted to fuse the spliced visible light image and the second image, so that the defogged spliced visible light image is obtained.

In still another possible implementation manner, the electronic device may further extract a pixel value of a feature point in the visible light image and a pixel value of a corresponding point in the second image, and then fuse the pixel values of the feature point in the visible light image according to the pixel value of the corresponding point in the second image, so as to enhance the image of the feature region in the visible light image and enhance the feature recognition effect of the visible light image.

In the above embodiment, based on the area array hyperspectral image, the defogging treatment is performed on the foggy visible light image based on the fusion method of the hyperspectral image and the visible light image, so that the definition of the visible light image can be improved, and the image quality can be further improved.

For a better understanding of the whole process of the method for generating an image provided in the embodiment of the present application, reference may also be made to an embodiment process shown in fig. 7, where the implementation process of each step may be referred to the description of the foregoing embodiment, and the implementation principle and technical effect are similar, and are not repeated herein.

Examples of the method for generating an image provided by the embodiments of the present application are described above in detail. It will be appreciated that the electronic device, in order to achieve the above-described functions, includes corresponding hardware and/or software modules that perform the respective functions. Those of skill in the art will readily appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is implemented as hardware or computer software driven hardware depends upon the particular application and design constraints imposed on the solution. Those skilled in the art may implement the described functionality using different approaches for each particular application in conjunction with the embodiments, but such implementation is not to be considered as outside the scope of this application.

The embodiment of the present application may divide the functional modules of the electronic device according to the above method examples, for example, may divide each function into each functional module corresponding to each function, for example, a detection unit, a processing unit, a display unit, or the like, or may integrate two or more functions into one module. The integrated modules may be implemented in hardware or in software functional modules. It should be noted that, in the embodiment of the present application, the division of the modules is schematic, which is merely a logic function division, and other division manners may be implemented in actual implementation.

It should be noted that, all relevant contents of each step related to the above method embodiment may be cited to the functional description of the corresponding functional module, which is not described herein.

The electronic device provided in this embodiment is configured to execute the method for generating an image, so that the same effects as those of the implementation method can be achieved.

In case an integrated unit is employed, the electronic device may further comprise a processing module, a storage module and a communication module. The processing module can be used for controlling and managing the actions of the electronic equipment. The memory module may be used to support the electronic device to execute stored program code, data, etc. And the communication module can be used for supporting the communication between the electronic device and other devices.

Wherein the processing module may be a processor or a controller. Which may implement or perform the various exemplary logic blocks, modules, and circuits described in connection with this disclosure. A processor may also be a combination that performs computing functions, e.g., including one or more microprocessors, digital signal processing (digital signal processing, DSP) and microprocessor combinations, and the like. The memory module may be a memory. The communication module can be a radio frequency circuit, a Bluetooth chip, a Wi-Fi chip and other equipment which interact with other electronic equipment.

In one embodiment, when the processing module is a processor and the storage module is a memory, the electronic device according to this embodiment may be a device having the structure shown in fig. 1.

The present application also provides a computer-readable storage medium in which a computer program is stored, which when executed by a processor, causes the processor to perform the method of generating an image of any of the above embodiments.

The present application also provides a computer program product which, when run on a computer, causes the computer to perform the above-described related steps to implement the method of generating an image in the above-described embodiments.

In addition, embodiments of the present application also provide an apparatus, which may be specifically a chip, a component, or a module, and may include a processor and a memory connected to each other; the memory is configured to store computer-executable instructions, and when the apparatus is running, the processor may execute the computer-executable instructions stored in the memory, so that the chip performs the method for generating an image in the above method embodiments.

The electronic device, the computer readable storage medium, the computer program product or the chip provided in this embodiment are used to execute the corresponding method provided above, so that the beneficial effects thereof can be referred to the beneficial effects in the corresponding method provided above, and will not be described herein.

It will be appreciated by those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional modules is illustrated, and in practical application, the above-described functional allocation may be performed by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules to perform all or part of the functions described above.

In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of modules or units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another apparatus, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and the parts shown as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed in a plurality of different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a readable storage medium. Based on such understanding, the technical solution of the embodiments of the present application may be essentially or a part contributing to the prior art or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, including several instructions to cause a device (may be a single-chip microcomputer, a chip or the like) or a processor (processor) to perform all or part of the steps of the methods of the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read Only Memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method of generating an image for use in an electronic device comprising an image acquisition device, the method comprising:

acquiring n first images and n first spectrum data acquired by the image acquisition device; wherein one of the first spectrum data corresponds to one of the first images, the first spectrum data is lattice hyperspectral data or linear hyperspectral data, and n is a positive integer greater than or equal to 2; the n first images and the n first spectrum data are obtained through multiple shooting of the user-held electronic equipment facing the target area;

determining registration parameters required for image registration of an ith first image, wherein i traverses 1 to n;

processing the ith first spectrum data by utilizing the registration parameters to obtain the ith second spectrum data; wherein the ith first spectral data is spectral data corresponding to the ith first image, the ith traversal 1 through n;

Generating a second image according to the obtained n second spectrum data, wherein the second image is an area array hyperspectral image.

2. The method according to claim 1, wherein said determining said registration parameters required for image registration of said i-th first image, in particular comprises:

selecting a j-th first image from the n first images as a reference image of the i-th first image, wherein the j-th first image is different from the i-th first image;

extracting features of the jth first image to obtain first feature points, extracting features of the ith first image to obtain second feature points, and determining matched feature point pairs according to the first feature points and the second feature points;

and determining the registration parameters of the ith first image according to the coordinate information of the matched characteristic point pairs.

3. The method of claim 2, wherein the jth first image is a previous frame image adjacent to the ith first image, the method further comprising:

performing image registration on the ith first image by using the registration parameters of the ith first image to obtain a registered ith first image; wherein the i-th first image after registration is used as a reference image of the i+1-th first image.

4. A method according to claim 2 or 3, wherein the image acquisition device comprises a TOF lens, and the determining the matched pair of feature points according to the first feature point and the second feature point specifically comprises:

acquiring first three-dimensional coordinate information of the first feature point and second three-dimensional coordinate information of the second feature point; the first three-dimensional coordinate information and the second three-dimensional coordinate information are obtained by calculation according to the acquired data of the TOF lens;

and matching the first characteristic points with the second characteristic points according to the first three-dimensional coordinate information and the second three-dimensional coordinate information, and determining the matched characteristic point pairs.

5. The method according to any one of claims 2-4, wherein an inertial sensor is configured in the electronic device, and before the feature extraction of the j-th first image to obtain the first feature point and the feature extraction of the i-th first image to obtain the second feature point, the method further comprises:

according to sensor data acquired by the inertial sensor when the image acquisition device acquires the jth first image, performing image optimization on the jth first image to obtain an optimized jth first image;

And according to the sensor data acquired by the inertial sensor when the image acquisition device acquires the ith first image, performing image optimization on the ith first image to obtain an optimized ith first image.

6. The method according to any one of claims 1-5, further comprising:

based on the second image, defogging the target image by adopting a preset algorithm to obtain a defogged target image; the target image is the ith first image or is a spliced image generated by performing image registration on the n first images.

7. An electronic device, comprising:

an image acquisition device;

one or more processors;

one or more memories;

a module in which a plurality of application programs are installed;

the memory stores one or more programs that, when executed by the processor, cause the electronic device to perform the steps of:

8. The electronic device of claim 7, wherein the one or more programs, when executed by the processor, cause the electronic device to perform the steps of:

9. The electronic device of claim 8, wherein the jth first image is a previous frame image adjacent to the ith first image, which when executed by the processor, causes the electronic device to perform the steps of:

10. The electronic device of claim 8 or 9, wherein the image acquisition apparatus comprises a TOF lens, which when executed by the processor, causes the electronic device to perform the steps of:

11. The electronic device of any of claims 8-10, wherein an inertial sensor is configured in the electronic device, which when executed by the processor causes the electronic device to perform the steps of:

12. The electronic device of any of claims 7-11, wherein the one or more programs, when executed by the processor, cause the electronic device to perform the steps of:

13. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program which, when executed by a processor, causes the processor to perform the method of any of claims 1 to 6.