CN114827442A

CN114827442A - Method and electronic device for generating image

Info

Publication number: CN114827442A
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: 2022-07-29
Anticipated expiration: 2041-01-29
Also published as: WO2022161011A1; CN114827442B

Abstract

The application relates to the field of terminal AI, in particular to the field of image generation, and provides a method for generating an image and electronic equipment, wherein the method comprises the following steps: acquiring n first images and n first spectral data acquired by an image acquisition device; the first spectrum data corresponds to a first image, the first spectrum data is dot matrix hyperspectral data or linear array hyperspectral data, and n is a positive integer greater than or equal to 2; determining registration parameters required when the ith first image is determined to perform image registration, wherein i traverses 1 to n; processing the ith first spectral data by using the registration parameters to obtain ith second spectral data, wherein the ith first spectral data is spectral data corresponding to the ith first image, and i traverses from 1 to n; and generating a second image according to the 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 is high in applicability.

Description

Method and electronic device for generating image

Technical Field

The present application relates to the field of Artificial Intelligence (AI) for terminals, in particular to the field of image generation, and more particularly to a method for generating an image and an electronic device.

Background

The hyperspectral imaging technology is a branch technology which is rapidly developed in the remote sensing technology, and through hyperspectral sensors carried on different space platforms, a target area is imaged simultaneously in tens of to hundreds of continuous and subdivided spectral bands in ultraviolet, visible light, near infrared and mid-infrared areas of an 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 type spectral sensor, and can scan a target to obtain single-point or linear array hyperspectral data and then generate an area array hyperspectral image through the single-point or linear array hyperspectral data. In the traditional technology, a push-broom type imaging method is mostly adopted, 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, so that an area array hyperspectral image is obtained.

However, it is difficult to incorporate the above-mentioned complicated mechanical device in an electronic device such as a mobile terminal, and thus the push-broom type imaging method in the conventional art is less applicable.

Disclosure of Invention

The application provides an image generation method and electronic equipment, assistance is not needed by means of complex mechanical equipment, the applicability is strong, and the capacity of the electronic equipment for generating an area array hyperspectral image is greatly improved.

In a first aspect, the present application provides a method for generating an image, which is applied to an electronic device including an image capturing apparatus, and includes: acquiring n first images and n first spectral data acquired by an image acquisition device; the first spectrum data corresponds to a first image, the first spectrum data is dot matrix hyperspectral data or linear array hyperspectral data, and n is a positive integer greater than or equal to 2; determining registration parameters required by the ith first image during image registration, wherein i traverses 1 to n; processing the ith first spectrum data by using the registration parameters to obtain ith second spectrum data; the ith first spectrum data is spectrum data corresponding to the ith first image, and i traverses from 1 to n; and generating a second image according to the n second spectrum data, wherein the second image is an area array hyperspectral image.

Wherein, image acquisition device can include visible light camera and hyperspectral sensor, and first image can be the visible light image, and second spectral data is for carrying out transform processing to first spectral data and obtaining, for example coordinate transformation etc..

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

With reference to the first aspect, in some implementations of the first aspect, the determining registration parameters required for image registration of the ith first image specifically includes: selecting a jth first image from the n first images as a reference image of an ith first image, wherein the jth first image is different from the ith first image; performing feature extraction on the jth first image to obtain a first feature point, performing feature extraction on the ith 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 the registration parameters of the ith first image according to the coordinate information of the matched characteristic point pairs.

In the implementation mode, the electronic device extracts features of the reference image and the ith first image to obtain matched feature point pairs, further determines registration parameters of the ith first image, provides data preparation for subsequent conversion processing of the dot matrix hyperspectral data or the linear array hyperspectral data, further does not need to be assisted by complex mechanical equipment, and is high in applicability.

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: carrying out image registration on the ith first image by using the registration parameter of the ith first image to obtain the registered ith first image; and taking the registered ith first image as a reference image of the (i + 1) th first image.

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

With reference to the first aspect, in some implementation manners of the first aspect, the determining, by the image acquisition apparatus, a matched feature point pair according to the first feature point and the second feature point includes: acquiring first three-dimensional coordinate information of the first characteristic point and second three-dimensional coordinate information of the second characteristic point; the first three-dimensional coordinate information and the second three-dimensional coordinate information are obtained by calculation according to the collected data of the TOF lens; and matching the first characteristic point and the second characteristic point according to the first three-dimensional coordinate information and the second three-dimensional coordinate information, and determining a matched characteristic point pair.

In the implementation mode, the electronic equipment adopts the three-dimensional coordinate information of the characteristic point pairs for matching, so that the precision of the matched characteristic point pairs can be improved, and the precision of the 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 performing feature extraction on the jth first image to obtain a first feature point and performing feature extraction on the ith first image to obtain a second feature point, the method further includes: performing image optimization on the jth first image according to sensor data acquired by an inertial sensor when the jth first image is acquired by an image acquisition device to obtain an optimized jth first image; and 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 to obtain the optimized ith first image.

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

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

In the implementation mode, on the basis of the area array hyperspectral image, the fog removal processing is carried out on the fog-containing image based on a hyperspectral image and visible light image fusion method, 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 behavior of the electronic device in the first aspect and the possible implementation manners of the first aspect. The functions may be implemented by hardware, or by hardware executing corresponding software. The hardware or software includes one or more modules or units corresponding to the above-described functions. Such as a processing module or unit, etc.

In a third aspect, the present application provides an 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 adapted to read and execute the 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, the memory being connected to the processor by 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, and when the computer program is executed by a processor, the processor is enabled to execute any one of the methods in the technical solutions of the first aspect.

In a sixth aspect, the present application provides a computer program product comprising: computer program code for causing an electronic device to perform any of the methods of the first aspect when the computer program code runs on the electronic device.

Drawings

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

FIG. 2 is a block diagram of a software architecture of an electronic device according to an embodiment of the present disclosure;

FIG. 3 is a system architecture diagram illustrating 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 disclosure;

FIG. 6 is a schematic flowchart of another example of a method for generating an image according to an embodiment of the present disclosure;

fig. 7 is a schematic 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. In the description of the embodiments herein, "/" means "or" unless otherwise specified, for example, a/B may mean a or B; "and/or" herein is merely an association describing an associated object, and means that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of the present application, "a plurality" means two or more than two.

In the following, the terms "first", "second" and "third" are used 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, features defined as "first", "second", "third" may explicitly or implicitly include one or more of the features.

Generally, in order to analyze spatial information of some target objects more deeply, two-dimensional geometric spatial information and one-dimensional spectral information of the target objects can be detected by means of a hyperspectral imaging technology, and continuous and narrow-band image data with a hyperspectral resolution can be acquired. The hyperspectral sensor is characterized in that the hyperspectral sensor is a single-point or linear array sensor, and when an area array hyperspectral image is generated based on single-point or linear array hyperspectral data, external mechanical equipment needs to be combined, a target object is scanned at a fixed push-broom speed, and then the single-point or linear array hyperspectral data are 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 embed a large-sized external mechanical device with high cost and low portability, and the above method is not suitable for the handheld device or the mobile device.

In view of this, an embodiment of the present disclosure provides a method for generating an image, which may be applied to an electronic device including an image acquisition apparatus, such as a mobile phone, a tablet computer, a wearable device, an in-vehicle device, an Augmented Reality (AR)/Virtual Reality (VR) device, a notebook computer, a super-mobile personal computer (UMPC), a netbook, and a Personal Digital Assistant (PDA). The image acquisition device can comprise a camera, a hyperspectral sensor and the like. The electronic equipment generates the area array hyperspectral image by utilizing the image registration information of the visible light image acquired by the image acquisition device and 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 the electronic device.

For example, fig. 1 is a schematic structural diagram of an example of an electronic device 100 provided in the 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 (USB) interface 130, a charging 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, a key 190, a motor 191, an indicator 192, a camera 193, a display screen 194, a Subscriber Identification Module (SIM) card interface 195, and the like. The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light 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 illustrated structure of the embodiment of the present application does not specifically limit the electronic device 100. In other embodiments of the present application, electronic device 100 may include more or fewer components than shown, or some components may be combined, some components may be split, or a different arrangement of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

Processor 110 may include one or more processing units, such as: the processor 110 may include an Application Processor (AP), a modem processor, a Graphics Processing Unit (GPU), an Image Signal Processor (ISP), a controller, a memory, a video codec, a Digital Signal Processor (DSP), a baseband processor, and/or a neural-Network Processing Unit (NPU), etc. The different processing units may be separate devices or may be integrated into one or more processors.

The controller may be, among other things, a neural center and a command center of the electronic device 100. The controller can generate an operation control signal according to the instruction operation code and the timing signal to complete the control of instruction fetching and instruction execution.

A memory may also be provided in 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 have just been used or recycled by the processor 110. If the processor 110 needs to reuse the instruction or data, it can be called directly from memory. Avoiding repeated accesses reduces the latency of the processor 110, thereby increasing the efficiency of the system.

In some embodiments, processor 110 may include one or more interfaces. The interface may include an integrated circuit (I2C) interface, an integrated circuit built-in audio (I2S) interface, a Pulse Code Modulation (PCM) interface, a 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 (SIM) interface, a bus or Universal Serial Bus (USB) interface, and the like.

The I2C interface is a bi-directional synchronous serial bus that includes a serial data line (SDA) and a Serial Clock Line (SCL). In some embodiments, processor 110 may include multiple sets of I2C buses.

The I2S interface may be used for audio communication. In some embodiments, processor 110 may include 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.

The PCM interface may also be used for audio communication, sampling, quantizing and encoding analog signals. In some embodiments, the audio module 170 and the wireless communication module 160 may be coupled by a PCM bus interface.

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

MIPI interfaces may be used to connect processor 110 with peripheral devices such as display screen 194, camera 193, and the like. The MIPI interface includes a Camera Serial Interface (CSI), a Display Serial Interface (DSI), and the like. In some embodiments, processor 110 and camera 193 communicate through a CSI interface to implement the capture functionality of electronic device 100. The processor 110 and the display screen 194 communicate through the DSI interface to implement the display function of the electronic device 100.

The GPIO interface may be configured by software. The GPIO interface may be configured as a control signal and may also be configured 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, a MIPI interface, and the like.

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 transmit data between the electronic device 100 and a peripheral device. And the earphone can also be used for connecting an earphone and playing audio through the earphone. The interface may also be used to connect other electronic devices, such as AR devices and the like.

It should be understood that the interface connection relationship between the modules illustrated in the embodiments of the present application is only an illustration, and does not limit the structure of the electronic device 100. In other embodiments of the present application, the electronic device 100 may also adopt different interface connection manners or a combination of multiple interface connection manners in the above embodiments.

The charging management module 140 is configured to receive charging input from a charger. The charger may be a wireless charger or a wired charger. In some wired charging embodiments, the charging management module 140 may receive charging input from a wired charger via the USB interface 130. In some wireless charging embodiments, the charging management module 140 may receive a 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 to connect the battery 142, the charging 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 used to monitor parameters such as battery capacity, battery cycle count, battery state of health (leakage, impedance), etc. In some other embodiments, the power management module 141 may also be disposed in the processor 110. In other embodiments, the power management module 141 and the charging 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 structure of the antenna 1 and the antenna 2 in fig. 1 is merely an example. The mobile communication module 150 may provide a solution including 2G/3G/4G/5G wireless communication applied to the electronic device 100. The mobile communication module 150 may include at least one filter, a switch, a power amplifier, a Low Noise Amplifier (LNA), and the like. The mobile communication module 150 may receive the electromagnetic wave from the antenna 1, filter, amplify, etc. the received electromagnetic wave, and transmit the electromagnetic wave to the modem processor for demodulation. The mobile communication module 150 may also amplify the signal modulated by the modem processor, and convert the signal into electromagnetic wave through the antenna 1 to radiate the electromagnetic wave.

The modem processor may include a modulator and a demodulator. The modulator is used for modulating a 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 passes the demodulated low frequency baseband signal to a 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 a sound signal through an audio device (not limited to the speaker 170A, the receiver 170B, etc.) or displays an image 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 modules, independent of the processor 110.

The wireless communication module 160 may provide a solution for wireless communication applied to the electronic device 100, including Wireless Local Area Networks (WLANs) (e.g., wireless fidelity (Wi-Fi) networks), bluetooth (bluetooth, BT), Global Navigation Satellite System (GNSS), Frequency Modulation (FM), Near Field Communication (NFC), Infrared (IR), and the like. The wireless communication module 160 may be one or more devices integrating at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via the antenna 2, performs frequency modulation and filtering processing on 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, perform frequency modulation and amplification on the signal, and convert the signal into electromagnetic waves through the antenna 2 to radiate the electromagnetic waves.

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

The display screen 194 is used to display images, video, and the like. The display screen 194 includes a display panel. The display panel may adopt a Liquid Crystal Display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode (active-matrix organic light-emitting diode, AMOLED), a flexible light-emitting diode (FLED), a miniature, a Micro-oeld, a quantum dot light-emitting diode (QLED), and the like. In some embodiments, the electronic device 100 may include 1 or N display screens 194, with N being a positive integer greater than 1.

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

The ISP is used to process the data fed back by the camera 193. For example, when a photo is taken, 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 and converting into an image visible to naked eyes. The ISP can also carry out algorithm optimization on 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 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 to the photosensitive element. The photosensitive element may be a Charge Coupled Device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The light sensing element converts the optical signal into an electrical signal, which is then passed to the ISP where it is converted into a digital image signal. And the ISP outputs the digital image signal to the DSP for processing. The DSP converts the digital image signal into image signal in standard RGB, YUV and other formats. In some embodiments, the 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 measure of the time it takes for an object, particle, or wave (e.g., acoustic, electromagnetic, etc.) to travel a distance in a medium. The TOF lens can transmit waves and receive the waves reflected by the photographed object after the waves encounter the photographed object. The electronic device may thus obtain the time difference of the TOF lens from transmitting a wave to receiving a reflected wave, and/or the phase difference between a wave transmitted by the TOF lens and a 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 that a 3D model or a 3D image containing the depth information of the shot object is obtained. Alternatively, the wave may be infrared light, laser pulses, ultrasonic waves, or the like.

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

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: moving Picture Experts Group (MPEG) 1, MPEG2, MPEG3, MPEG4, and the like.

The NPU is a neural-network (NN) computing processor that processes input information quickly by using a biological neural network structure, for example, by using a transfer mode between neurons of a human brain, and can also learn by itself continuously. Applications such as intelligent recognition of the electronic device 100 can be realized through the NPU, for example: image recognition, face recognition, speech recognition, text understanding, and the like.

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

The internal memory 121 may be used to store computer-executable program code, which 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 program storage area and a data storage area. The storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required by at least one function, and the like. The storage data area may store data (such as audio data, phone book, etc.) created during use of the electronic device 100, and the like. 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 (UFS), and the like.

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

The pressure sensor 180A is used for sensing a pressure signal, and converting 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 can be of a wide variety, such as a resistive pressure sensor, an inductive pressure sensor, a capacitive pressure sensor, and the like. The capacitive pressure sensor may be a sensor comprising at least two parallel plates having an electrically conductive material. When a force acts on the pressure sensor 180A, the capacitance between the electrodes changes. 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 intensity of the touch operation according to the pressure sensor 180A. The electronic apparatus 100 may also calculate the touched position from the detection signal of the pressure sensor 180A. In some embodiments, the touch operations that are applied to the same touch position but different touch operation intensities may correspond to different operation instructions. For example: and when the touch operation with the touch operation intensity smaller than the first pressure threshold value acts on the short message application icon, executing an instruction for viewing the short message. And when the touch operation with the touch operation intensity larger than or equal to the first pressure threshold value acts on the short message application icon, executing an instruction of newly building the short message.

The gyro sensor 180B may be used to determine the motion attitude of the electronic device 100. In some embodiments, the angular velocity of electronic device 100 about three axes (i.e., the x, y, and z axes) may be determined by gyroscope 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 a shake angle of the electronic device 100, calculates a distance to be compensated for by the lens module according to the shake angle, and allows the lens to counteract the shake of the electronic device 100 through a reverse movement, thereby achieving anti-shake. The gyroscope sensor 180B may also be used for navigation, somatosensory gaming scenes.

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

The magnetic sensor 180D includes a hall sensor. The electronic device 100 may detect the opening and closing of the flip holster using the magnetic sensor 180D. In some embodiments, when the electronic device 100 is a flip phone, the electronic device 100 may detect the opening and closing of the flip according to the magnetic sensor 180D. And then according to the opening and closing state of the leather sheath or the opening and closing state of the flip cover, the automatic unlocking of the flip cover is 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 can be detected when the electronic device 100 is stationary. The method can also be used for recognizing the posture 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, taking a picture of a scene, electronic device 100 may utilize range sensor 180F to range for fast 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 to the outside 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 can be determined that there is an object near the electronic device 100. When insufficient reflected light is detected, the electronic device 100 may determine that there are no objects near the electronic device 100. The electronic device 100 can utilize the proximity light sensor 180G to detect that the user holds the electronic device 100 close to the ear for talking, so as to automatically turn off the screen to achieve the purpose of saving power. The proximity light sensor 180G may also be used in a holster mode, a pocket mode automatically unlocks and locks the screen.

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

The fingerprint sensor 180H is used to collect a fingerprint. The electronic device 100 can utilize the collected fingerprint characteristics to unlock the fingerprint, access the application lock, photograph the fingerprint, answer an incoming call with the fingerprint, and so on.

The temperature sensor 180J is used to detect temperature. In some embodiments, electronic device 100 implements a temperature processing strategy using the temperature detected by temperature sensor 180J.

The touch sensor 180K is 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 used to detect a touch operation applied thereto or nearby. The touch sensor can communicate the detected touch operation to the application processor to determine the touch event type. Visual output associated with the touch operation may be provided through the display screen 194. In other embodiments, the touch sensor 180K may be disposed on a surface of the electronic device 100, different from the position of the display screen 194.

The bone conduction sensor 180M may acquire a vibration signal. In some embodiments, the bone conduction sensor 180M may acquire a vibration signal of the human vocal part vibrating the bone mass. The bone conduction sensor 180M may also contact the human pulse to receive the blood pressure pulsation signal. In some embodiments, the bone conduction sensor 180M may also be disposed in a headset, integrated into a bone conduction headset. The audio module 170 may analyze a voice signal based on the vibration signal of the bone mass vibrated by the sound part acquired by the bone conduction sensor 180M, so as to implement a voice function. The application processor can analyze heart rate information based on the blood pressure beating signals acquired by the bone conduction sensor 180M, and the heart rate detection function is realized.

In some embodiments, the electronic device 100 further includes a hyperspectral sensor, which may be a dot-matrix sensor or a linear-matrix sensor, the dot-matrix sensor may acquire dot-matrix hyperspectral data, and the linear-matrix sensor may acquire linear-matrix hyperspectral data.

The keys 190 include a power-on key, a volume key, and the like. The keys 190 may be mechanical keys. Or may be touch keys. The electronic apparatus 100 may receive a key input, and generate a key signal input related to user setting and function control of the electronic apparatus 100.

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

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

The SIM card interface 195 is used to connect a SIM card. The SIM card can be brought into and out of contact with the electronic apparatus 100 by being inserted into the SIM card interface 195 or being pulled out of the SIM card interface 195. 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 micro-core architecture, a micro-service architecture, or a cloud architecture. The embodiment of the present application takes an Android system with a layered architecture as an example, and exemplarily illustrates a software structure of the electronic device 100.

Fig. 2 is a block diagram of a software structure of the electronic device 100 according to the embodiment of the present application. The layered architecture divides the software into several layers, each layer having a clear role and division of labor. The layers communicate with each other through a software interface. In some embodiments, the Android system is divided into four layers, an application layer, an application framework layer, an Android runtime (Android runtime) and system library, and a kernel layer from top to bottom. The application layer may include a series of application packages.

As shown in fig. 2, the application package may include applications such as camera, gallery, calendar, phone call, map, navigation, WLAN, bluetooth, music, video, short message, etc.

The application framework layer provides an Application Programming Interface (API) and a programming framework for the application program of the application layer. The application framework layer includes a number of predefined functions.

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

The window manager is used for managing window programs. The window manager can obtain 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 it accessible to applications. The data may include video, images, audio, calls made and received, browsing history and bookmarks, phone books, 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, the display interface including the short message notification icon may include a view for displaying text and a view for displaying pictures.

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

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

The notification manager enables the application to display notification information in the status bar, can be used to convey notification-type messages, can disappear automatically after a short dwell, and does not require user interaction. Such as a notification manager used to inform download completion, message alerts, etc. The notification manager may also be a notification that appears in the form of a chart or scroll bar text at the top status bar of the system, 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, prompting text information in the status bar, sounding a prompt tone, vibrating the electronic device, flashing an indicator light, etc.

The Android runtime comprises a core library and a virtual machine. The Android runtime is responsible for scheduling and managing an Android system.

The core library comprises 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. And executing java files of the application program layer and the application program framework layer into a binary file by the virtual machine. The virtual machine is used for performing the functions of object life cycle management, stack management, thread management, safety and exception management, garbage collection and the like.

The system library may include a plurality of functional modules. For example: surface managers (surface managers), media libraries (media libraries), three-dimensional graphics processing libraries (e.g., OpenGL ES), 2D graphics engines (e.g., SGL), and the like.

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

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

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 convenience of understanding, the following embodiments of the present application will specifically describe, by taking an electronic device having a structure shown in fig. 1 and fig. 2 as an example, a method for generating an image provided by the embodiments of the present application with reference to the drawings.

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

When a user holds the electronic equipment and shoots for multiple times facing a 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 dot matrix hyperspectral data or linear array hyperspectral data. For convenience of description, the following description will be made by taking linear array type hyperspectral data as an example.

After the electronic device acquires the plurality of visible light images, image registration can be performed on the plurality of visible light images to obtain registration parameters during image registration. Taking the 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 obtain a registration parameter of spatial coordinate transformation between the image a and the image B according to the feature point pair, as shown in fig. 3, where the registration parameter may be a spatial coordinate transformation matrix, which is simply referred to as a transformation matrix. The image preprocessing includes, but is not limited to, a process of correcting the image based on camera parameters and distortion parameters. The characteristic points of the image can be determined by extracting the characteristics of pixel points in the image, and the characteristics of the pixel points can comprise point characteristics, line characteristics and surface characteristics; the extraction algorithm of the point feature may include, but is not limited to, scale-invariant feature transform (SIFT) algorithm, surf (speeded up robust features) algorithm, and orb (oriented fast and rolling brief) algorithm, the extraction algorithm of the line feature may include, but is not limited to, log algorithm and canny algorithm, and the extraction algorithm of the surface feature may include, but is not limited to, region segmentation algorithm. Algorithms for feature point matching include, but are not limited to, Euclidean distance algorithm, nearest neighbor (KNN), Hamming distance algorithm, and similarity metric algorithm. Algorithms for solving the transformation matrix include, but are not limited to, random sample consensus (RANSAC) algorithm, RHO algorithm, Least Median (LMEDS) algorithm, and least squares algorithm.

In the method for generating the image, the electronic device performs coordinate conversion on the linear array hyperspectral data by using the registration parameter, and performs splicing processing on the linear array hyperspectral data after the coordinate conversion, so that an area array hyperspectral image is obtained, and the technical effect that the area array hyperspectral image can be generated without external mechanical equipment is achieved.

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

Further, the electronic device may 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 performing defogging processing on the spliced visible light image based on the area array hyperspectral image may include processes of fog concentration estimation, image partitioning, image fusion, image filtering and the like, and specific implementation processes may be referred to in the following method embodiments.

Optionally, the electronic device may further improve the precision of the registration parameter by using 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 precision of the obtained area array hyperspectral image. As described above, through the process of transmitting and receiving reflected waves by the TOF lens, the electronic device can calculate the depth information of the object to be shot; the collected data of the hardware sensor may include acceleration of the electronic device, and the like.

With regard to the method for generating an image provided in the embodiment of the present application, it is specifically described below. Fig. 4 is a schematic 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 spectral data acquired by an image acquisition device; the first spectrum data corresponds to a first image, the first spectrum data is lattice hyperspectral data or linear array 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 above embodiment of fig. 1, the visible light camera can acquire a visible light image (i.e., a first image), and the hyperspectral sensor can acquire dot matrix hyperspectral data or linear array hyperspectral data (i.e., first spectral data). When a user holds the electronic equipment and shoots for one time facing to the target area, the electronic equipment can simultaneously acquire a visible light image and first spectrum data. Therefore, in the continuous shooting or panoramic shooting mode, the electronic device can acquire a plurality of (e.g., n) 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 consistent with that of the hyperspectral sensor. The process of camera imaging is generally a process of converting a world coordinate system into a pixel coordinate system, namely a world coordinate system (3d) -a camera coordinate system (3d) -a picture plane coordinate system (2d) -a pixel coordinate system (2 d). After such a level of conversion, the coordinates of the target region in space are converted into pixel coordinates in the image. Optionally, after the visible light image is obtained, the electronic device may further perform correction preprocessing on the visible light image based on the camera internal parameter and the distortion parameter.

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

S102, determining a registration parameter required when the ith first image is subjected to image registration, wherein i traverses from 1 to n.

Specifically, after acquiring the 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, the coordinate transformation can be carried out on the pixel point coordinate in the visible light image so as to complete the image registration; in this embodiment, based on the transformation matrix, coordinate transformation may be performed on the first spectrum data to obtain second spectrum data.

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

In another possible implementation manner, any one of the n visible light images can be used as a reference image of the rest n-1 images, and the registration parameters corresponding to the rest n-1 visible light images are determined. For example, the 1 st visible light image is selected as a reference image, and the 2 nd to nth visible light images are all 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 ith second spectrum data; wherein the ith first spectral data is spectral data corresponding to the ith first image.

Each first spectrum data corresponds to one visible light image, and the transformation between the first spectrum data and the visible light image is relatively synchronous, so that the electronic equipment can process the first spectrum data by adopting the registration parameters corresponding to the visible light images, namely, the registration parameters of the ith visible light image are adopted to process the first spectrum data corresponding to the ith visible light image, and the second spectrum data is obtained. By way of example and not limitation, the registration parameter of the ith visible light image may be used to perform coordinate transformation on 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 may be obtained.

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

Specifically, if the corresponding second spectrum data is obtained for each first spectrum data, n second spectrum data are obtained in total, and the n second spectrum data are still dot matrix hyperspectral data or linear array hyperspectral data, so that the electronic device can splice the n second spectrum data to generate an area array hyperspectral image.

In the above embodiment, the electronic device transforms the point array hyperspectral data or the linear array hyperspectral data by using the registration parameters required during 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 the assistance of complex mechanical equipment, has strong applicability, and greatly improves the capacity of 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 image registration for the ith first image in S102 may include:

s201, selecting a jth first image in the n first images as a reference image of an ith first image, wherein the jth first image is different from the ith 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, the (i-1) th visible light image or any remaining visible light image is selected as the reference image of the ith visible light image. Further, the jth visible light image may also be a previous frame image adjacent to the ith visible light image, that is, j may be i-1, and then, after the electronic device performs image registration on the ith first image by using the registration parameter of the ith first image to obtain a registered ith first image, the electronic device may use the registered ith first image 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 1 st visible light image in the spatial domain, the registered 2 nd visible light image is used as a reference image, the 3 rd visible light image is registered to the spatial domain, the registered 3 rd visible light image is used as a reference image, the registered 4 th visible light image is registered to the spatial domain, and the like, so that the n visible light images can be registered to the same spatial domain, and the accuracy of the visible light images in image registration is improved.

S202, performing feature extraction on the jth first image to obtain a first feature point, performing feature extraction on the ith 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 S203, determining a registration parameter of the ith first image according to the coordinate information of the matched characteristic point pair.

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

As an example and not by way of limitation, the process of determining the registration parameters is described by taking the image registration of the 1 st visible light image a (reference image) and the 2 nd visible light image B as an example: firstly, the features of each pixel point in the image a and the features of each pixel point in the image B are extracted to determine a first feature point in the image a and a second feature point in the image B, and optionally, the pixel point features may include a point feature, a line feature and a plane feature. Then, feature point matching is performed based on the first feature points of the image a and the second feature points of the image B, and matched feature point pairs are 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, suppose (a, B) is a matched pair of feature points, where a is a feature point of image a, B is a feature point of image B, and let a have coordinates of (x) ₁ ，y ₁ ) B has the coordinate of (x) ₂ ，y ₂ ) Then there is a matrix H such that (x) ₁ ,y ₁ )＝H×(x ₂ ,y ₂ ) Then H is the transformation matrix, i.e. registration parameters, used when registering image B to image a. It should be noted that, for 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, and details are not described here again.

In the above embodiment, the electronic device performs feature extraction on the reference image and the ith visible light image to obtain matched feature point pairs, and then determines registration parameters of the ith visible light image, so as to provide data preparation for subsequent conversion processing of the dot matrix hyperspectral data or the linear array hyperspectral data, and further, the electronic device does not need to be assisted by complex mechanical equipment, and has strong applicability.

In addition, to improve the accuracy of the registration parameter determined in the foregoing embodiment, in an embodiment, the image acquisition apparatus further includes a TOF lens described in the foregoing embodiment of fig. 1, the three-dimensional coordinate information of each pixel point in the visible light image can be obtained through calculation according to the acquired data of the TOF lens, and accordingly, the electronic device can obtain the three-dimensional coordinate information of the first feature point and the coordinate information of the second feature point, and the determining a matched feature point pair according to the first feature point and the second feature point in S202 may include: according to the three-dimensional coordinate information of the first characteristic point and the three-dimensional coordinate information of the second characteristic point, the first characteristic point and the second characteristic point are matched by using algorithms such as an Euclidean distance algorithm, a KNN algorithm, a Hamming distance algorithm or a similarity measurement algorithm in the embodiment, and the matched characteristic point pair is determined, so that the precision of the matched characteristic point pair is improved, and the precision of the registration parameter 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 jitter or other factors, so that the embodiment of the present application may further optimize the collected visible light image, and then perform the process of extracting the features to obtain the feature points in S202. Optionally, the electronic device may be configured with an inertial sensor, such as an accelerometer, a gyroscope, and the like, where the inertial sensor may acquire sensor data representing a motion state of the electronic device in real time, and when the image acquisition device acquires an ith visible light image, the inertial sensor may also acquire sensor data at a corresponding time, and when the image acquisition device acquires a jth visible light image, the inertial sensor may also acquire sensor data at a corresponding time; then, the electronic device can perform image optimization on the jth visible light image according to sensor data acquired by the inertial sensor when the jth visible light image is acquired by the image acquisition device, so as to obtain an optimized jth visible light image; and performing image optimization on the ith visible light image according to sensor data acquired by the inertial sensor when the image acquisition device acquires the ith visible light image to obtain the optimized ith visible light image.

Specifically, the description will be given taking an example of image optimization of the i-th visible light image. The inertial sensor can acquire the three-axis angular velocity and the three-axis acceleration of the electronic equipment. The electronic device can use a Kalman filtering method to filter the three-axis angular velocity and the three-axis acceleration, convert the three-axis angular velocity into an Euler angle by using an Euler dynamics equation, and convert the three-axis acceleration into three-axis displacement by using a uniform acceleration motion formula, so as to obtain a rotation matrix and a translation matrix. Next, the electronic device may calculate a background optical flow of the ith visible light image according to the rotation matrix and the translation matrix, and perform robustness estimation on the background optical flow of the ith visible light image by using a RANSAC algorithm to eliminate a moving optical flow existing in the background optical flow, thereby completing image optimization on the ith visible light image. The process of the electronic device performing image optimization on the jth visible light image is similar to the process of performing image optimization on the ith visible light image, and is not described herein again.

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 precision of the obtained registration parameters can be further improved, on the basis, the point array hyperspectral data or the linear array hyperspectral data is transformed, and the precision of the obtained area array hyperspectral image can be improved.

For another practical application scenario, if the external environment is poor when the image acquisition device acquires the visible light image, and if the image acquisition device acquires the visible light image, the acquired visible light image is not high 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 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 a 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 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 brightness values of corresponding pixels from a blue light channel of an ith visible light image and a second image, determine fog concentration distribution according to a difference between the brightness values of the corresponding pixels, then fuse the brightness values of corresponding pixels in the second image and the ith visible light image according to the fog concentration distribution to obtain defogging brightness values, and finally generate an ith defogged visible light image according to the defogging brightness values and corresponding color values in the ith visible light image. Optionally, the electronic device may further continue to 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 to obtain a defogged target image, where the target image is a stitched image generated after the image registration is performed on the n visible light images.

Specifically, after determining registration parameters required for image registration for n visible light images, the electronic device may perform coordinate transformation on pixel coordinates of an ith visible light image based on the registration parameters of the ith visible light image to obtain an i registered visible light image, and then perform image stitching on the n registered visible light images to generate a stitched visible light image; for example, the plurality of partial visible light images are stitched into a panoramic visible light image. And then, fusing the spliced visible light image and the second image by adopting the visible light near-infrared image fusion algorithm in the embodiment to obtain the defogged spliced visible light image.

In yet another possible implementation manner, the electronic device may further extract pixel values of the feature points in the visible light image and pixel values of corresponding points in the second image, and then fuse the pixel values of the feature points in the visible light image according to the pixel values of the corresponding points in the second image, so as to perform image enhancement on the feature region in the visible light image, and enhance the feature recognition effect of the visible light image.

In the above embodiment, on the basis of the area array hyperspectral image, the visible light image containing fog is subjected to defogging processing based on the hyperspectral image and visible light image fusion method, so that the definition of the visible light image can be improved, and the image quality is further improved.

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

An example of a method for generating an image provided by an embodiment of the present application is described above in detail. It will be appreciated that the electronic device, in order to implement the above-described functions, comprises corresponding hardware and/or software modules for performing the respective functions. Those of skill in the art would readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, with the embodiment described in connection with the particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiment of the present application, the electronic device may be divided into the functional modules according to the method example, for example, the functional modules may be divided into the functional modules corresponding to the functions, such as the detection unit, the processing unit, the display unit, and the like, or two or more functions may be integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. It should be noted that, in the embodiment of the present application, the division of the module is schematic, and is only one logic function division, and there may be another division manner in actual implementation.

It should be noted that all relevant contents of each step related to the method embodiment may be referred to the functional description of the corresponding functional module, and are not described herein again.

The electronic device provided by the embodiment is used for executing the method for generating the image, so that the same effect as the implementation method can be achieved.

In case of an integrated unit, 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 action of the electronic equipment. The memory module may be used to support the electronic device in executing stored program codes and data, etc. The communication module can be used for supporting the communication between the electronic equipment and other equipment.

The processing module may be a processor or a controller. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. A processor may also be a combination of computing functions, e.g., a combination of one or more microprocessors, a Digital Signal Processing (DSP) and a microprocessor, or the like. The storage module may be a memory. The communication module may specifically be a radio frequency circuit, a bluetooth chip, a Wi-Fi chip, or other devices that interact with other electronic devices.

In an 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.

Embodiments of the present application further provide a computer-readable storage medium, in which a computer program is stored, and when the computer program is executed by a processor, the processor is caused to execute the method for generating an image according to any one of the above embodiments.

The embodiment of the present application further provides a computer program product, which when running on a computer, causes the computer to execute the above related steps to implement the method for generating an image in the above embodiment.

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 used for storing computer execution instructions, and when the device runs, the processor can execute the computer execution instructions stored in the memory, so that the chip can execute the method for generating the image in the above-mentioned method embodiments.

The electronic device, the computer-readable storage medium, the computer program product, or the chip provided in this embodiment are all configured to execute the corresponding method provided above, so that the beneficial effects achieved by the electronic device, the computer-readable storage medium, the computer program product, or the chip may refer to the beneficial effects in the corresponding method provided above, and are not described herein again.

Through the description of the above embodiments, those skilled in the art will understand that, for convenience and simplicity of description, only the division of the above functional modules is used as an example, and in practical applications, the above function distribution may be completed by different functional modules as needed, that is, the internal structure of the device may be divided into different functional modules to complete all or part of the above described functions.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, a module or a unit may be divided into only one logic function, and may be implemented in other ways, for example, a plurality of units or components may be combined or integrated into another apparatus, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

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

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application may be essentially or partially contributed to by the prior art, or all or part of the technical solutions may be embodied in the form of a software product, where the software product is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the methods of the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

The above description is only for the 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 conceive of the changes or substitutions within the technical scope of the present application, and shall 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 for generating an image, which is applied to an electronic device comprising an image acquisition device, is characterized in that the method comprises the following steps:

acquiring n first images and n first spectral data acquired by the image acquisition device; one piece of first spectrum data corresponds to one piece of first image, the first spectrum data is dot matrix hyperspectral data or linear array hyperspectral data, and n is a positive integer greater than or equal to 2;

determining registration parameters required when the ith first image is subjected to image registration, wherein i traverses from 1 to n;

processing the ith first spectrum data by using the registration parameters to obtain ith second spectrum data; wherein the ith first spectral data is spectral data corresponding to the ith first image, and the i traverses from 1 to n;

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

2. The method according to claim 1, wherein the determining the registration parameters required for image registration of the ith first image specifically comprises:

selecting a jth first image from the n first images as a reference image of the ith first image, wherein the jth first image is different from the ith first image;

performing feature extraction on the jth first image to obtain a first feature point, performing feature extraction on the ith 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 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 parameter of the ith first image to obtain an ith registered first image; wherein the registered ith first image is used as a reference image of the (i + 1) th first image.

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

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

and matching the first characteristic point and the second characteristic point according to the first three-dimensional coordinate information and the second three-dimensional coordinate information to determine the matched characteristic point pair.

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 jth first image to obtain the first feature point and the feature extraction of the ith first image to obtain the second feature point, the method further comprises:

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

and carrying out image optimization on the ith first image according to the sensor data acquired by the inertial sensor when the image acquisition device acquires the ith first image to obtain the optimized ith first image.

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

based on the second image, carrying out defogging treatment on the target image by adopting a preset algorithm to obtain a defogged target image; the target image is the ith first image, or the target image is a stitched image generated after image registration is performed on the n first images.

7. An electronic device, comprising:

an image acquisition device;

one or more processors;

one or more memories;

a module installed with a plurality of applications;

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, and wherein the one or more programs, when executed by the processor, cause 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, and wherein the one or more programs, when executed by the processor, cause the electronic device to perform the steps of:

11. The electronic device of any of claims 8-10, wherein the electronic device is configured with an inertial sensor, and wherein the one or more programs, when executed by the processor, cause 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, in which a computer program is stored which, when executed by a processor, causes the processor to carry out the method of any one of claims 1 to 6.