Patent Publication Number: US-2023156330-A1

Title: Method and apparatus for active reduction of mechanically coupled vibration in microphone signals

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of U.S. Application No. 17/502,013, filed on Oct. 14, 2021, which is a continuation of U.S. Application No. 16/710,902, filed on Dec. 11, 2019, now U.S. Pat. No. 11,153,487, the entire disclosures of which are hereby incorporated by reference. 
    
    
     TECHNICAL FIELD 
     This disclosure relates to noise reduction for electronic devices. 
     BACKGROUND 
     Microphones in electronic devices are prone to detect unwanted structural vibration noise in addition to detecting desirable acoustic vibrations. Typical solutions to reduce unwanted structural vibration noise include the use of mechanical isolation devices such as dampeners. Mechanical isolation devices can add to the weight of the electronic devices. In addition, mechanical isolation devices can limit the design of the electronic devices due to size constraints. It would be desirable to have a method and apparatus to reduce unwanted structural vibration noise in microphone signals using sensor data. 
     SUMMARY 
     Disclosed herein are implementations of a method and apparatus for active reduction of mechanically coupled vibration in electronic devices. In an aspect, an image capture device may include a microphone, a vibration sensor, and a processor. The microphone may be configured to obtain a microphone signal. The microphone signal may include an acoustic signal portion and a noise portion. The vibration sensor may be configured to obtain a vibration signal. The processor may be configured to receive the microphone signal, the vibration signal, or both. The processor may be configured to upsample the vibration signal. The processor may be configured to determine a correlation value. The correlation value may be based on the microphone signal, the upsampled vibration signal, or both. The processor may be configured to determine filter coefficients. The filter coefficients may be referred to as a set of filter coefficients. The filter coefficients may be determined based on the correlation value being above a threshold. The filter coefficient may be based on the upsampled vibration signal. The processor may be configured to filter the vibration signal based on the filter coefficients to remove the noise portion of the microphone signal and obtain a processed microphone signal. The processor may be configured to output the processed microphone signal. 
     In another aspect, an image capture device may include a microphone, a vibration sensor, and a processor. The microphone may be configured to obtain a microphone signal at a first sampling rate. The microphone signal may include an acoustic signal portion and a noise portion. The vibration sensor may be configured to obtain a vibration signal at a second sampling rate. The second sampling rate may be less than the first sampling rate. The processor may be configured upsample the vibration signal. The processor may be configured to determine a correlation value. The correlation value may be based on the microphone signal, the upsampled vibration signal, or both. The processor may be configured to filter the vibration signal based on the filter coefficients to remove the noise portion of the microphone signal and obtain a processed microphone signal. The processor may be configured to output the processed microphone signal. 
     In another aspect, a method may be implemented in an electronic device to reduce unwanted structural vibration noise in microphone signals. The method may include obtaining a microphone signal. The microphone signal may include an acoustic signal portion, a noise portion, or both. The method may include obtaining a vibration signal. The method may include upsampling the vibration signal. The method may include determining a correlation value. The correlation value may be based on the microphone signal, the upsampled vibration signal, or both. The method may include determining filter coefficients. The filter coefficients may be based on the upsampled vibration signal. The method may include filtering the vibration signal based on the filter coefficients to remove the noise portion of the microphone signal and obtain a processed microphone signal. The method may include outputting the processed microphone signal. 
     In another aspect, an integrated circuit may include a processor that is configured to upsample a vibration signal to obtain an upsampled vibration signal. The upsampled vibration signal may have one or more axial components. The processor may be configured to determine correlation values for the one or more axial components. A respective axial component may have a corresponding correlation value based on a microphone signal, the upsampled vibration signal, or both. The processor may be configured to determine filter coefficients based on the upsampled vibration signal if a correlation value is above a threshold. The processor may be configured to filter the axial component corresponding to a determined highest correlation value from amongst the correlation values of the upsampled vibration signal based on the filter coefficients to remove a mechanical noise portion of the microphone signal and obtain a processed microphone signal. The processor may be configured to output the processed microphone signal. 
     In another aspect, a method may include upsampling a vibration signal to obtain an upsampled vibration signal. The upsampled vibration signal may have one or more axial components. The method may include determining correlation values for the one or more axial components. A respective axial component may have a corresponding correlation value based on a microphone signal, the upsampled vibration signal, or both. The method may include determining filter coefficients. The filter coefficients may be determined based on the upsampled vibration signal when a correlation value from the correlation values is above a threshold. The method may include filtering the axial component corresponding to a determined highest correlation value from amongst the correlation values of the upsampled vibration signal based on the filter coefficients to remove a mechanical noise portion of the microphone signal and obtain a processed microphone signal. The method may include outputting the processed microphone signal. 
     In another aspect, an image capture device may include a processor that is configured to upsample a vibration signal to obtain an upsampled vibration signal. The upsampled vibration signal may have one or more axial components. The processor may be configured to determine correlation values for the one or more axial components. A respective axial component may have a corresponding correlation value. The corresponding correlation value may be based on a microphone signal, the upsampled vibration signal, or both. The processor may be configured to filter the axial component corresponding to a determined highest correlation value from amongst the correlation values of the upsampled vibration signal based on filter coefficients to remove a mechanical noise portion of the microphone signal and obtain a processed microphone signal. The processor may be configured to output the processed microphone signal. 
     In another aspect, an integrated circuit may include a processor that is configured to upsample a vibration signal to obtain an upsampled vibration signal. The upsampled vibration signal may have one or more axial components. The processor may be configured to determine correlation values for the one or more axial components. A respective axial component may have a corresponding correlation value based on a microphone signal, the upsampled vibration signal, or both. The processor may be configured to filter the axial component corresponding to a determined highest correlation value from amongst the correlation values of the upsampled vibration signal to remove a mechanical noise portion of the microphone signal and obtain a processed microphone signal. The processor may be configured to output the processed microphone signal. 
     In another aspect, a method may include upsampling a vibration signal to obtain an upsampled vibration signal. The upsampled vibration signal may have one or more axial components. The method may include determining correlation values for the one or more axial components. A respective axial component may have a corresponding correlation value based on a microphone signal, the upsampled vibration signal, or both. The method may include filtering the axial component corresponding to a determined highest correlation value from amongst the correlation values of the upsampled vibration signal to remove a mechanical noise portion of the microphone signal and obtain a processed microphone signal. The method may include outputting the processed microphone signal. 
     In another aspect, an image capture device may include a processor that is configured to upsample a vibration signal to obtain an upsampled vibration signal. The upsampled vibration signal may have one or more axial components. The processor may be configured to determine correlation values for the one or more axial components. A respective axial component may have a corresponding correlation value. The corresponding correlation value may be based on a microphone signal, the upsampled vibration signal, or both. The processor may be configured to determine a highest correlation value from amongst the correlation values. The processor may be configured to filter the axial component corresponding to the determined highest correlation value to remove a mechanical noise portion of the microphone signal and obtain a processed microphone signal. The processor may be configured to output the processed microphone signal. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The disclosure is best understood from the following detailed description when read in conjunction with the accompanying drawings. It is emphasized that, according to common practice, the various features of the drawings are not to-scale. On the contrary, the dimensions of the various features are arbitrarily expanded or reduced for clarity. 
         FIGS.  1 A-D  are isometric views of an example of an image capture device. 
         FIGS.  2 A-B  are isometric views of another example of an image capture device. 
         FIG.  2 C  is a cross-sectional view of the image capture device of  FIGS.  2 A-B . 
         FIGS.  3 A-B  are block diagrams of examples of image capture systems. 
         FIG.  4 A  is a diagram of a top-view of an image capture device in accordance with embodiments of this disclosure. 
         FIG.  4 B  is a diagram of a front-view of the image capture device shown in  FIG.  4 A  in accordance with embodiments of this disclosure. 
         FIG.  4 C  is a diagram of a rear-view of the image capture device shown in  FIG.  4 A  in accordance with embodiments of this disclosure. 
         FIG.  5    is a flow diagram of an example of a method for reducing vibration noise. 
         FIG.  6   . is a flow diagram of another example of a method for reducing vibration noise. 
         FIG.  7    is a block diagram of an example of an integrated circuit for reducing vibration noise. 
         FIG.  8    is a diagram of example plots of correlation values of microphone and IMU signals. 
     
    
    
     DETAILED DESCRIPTION 
     In the implementations described herein, the level of unwanted structural vibration noise may be reduced in the captured microphone signal using data from a vibration sensor. The vibration sensor may be used in conjunction with a microelectromechanical system (MEMS) microphone, an active noise cancellation system, or both. The vibration sensor may be configured to detect mechanical vibration without detecting acoustic vibration. The detected mechanical vibration may be used as an error signal in an adaptive filter. 
       FIGS.  1 A-D  are isometric views of an example of an image capture device  100 . The image capture device  100  may include a body  102  having a lens  104  structured on a front surface of the body  102 , various indicators on the front of the surface of the body  102  (such as LEDs, displays, and the like), various input mechanisms (such as buttons, switches, and touch-screen mechanisms), and electronics (e.g., imaging electronics, power electronics, etc.) internal to the body  102  for capturing images via the lens  104  and/or performing other functions. The image capture device  100  may be configured to capture images and video and to store captured images and video for subsequent display or playback. 
     The image capture device  100  may include various indicators, including LED lights  106  and LCD display  108 . The image capture device  100  may also include buttons  110  configured to allow a user of the image capture device  100  to interact with the image capture device  100 , to turn the image capture device  100  on, to operate latches or hinges associated with doors of the image capture device  100 , and/or to otherwise configure the operating mode of the image capture device  100 . The image capture device  100  may also include a microphone  112  configured to receive and record audio signals in conjunction with recording video. The image capture device  100  may also include a drain microphone  112 A configured to receive and record audio signals in conjunction with recording video. 
     The image capture device  100  may include an I/O interface  114  (e.g., hidden as indicated using dotted lines). As best shown in  FIG.  1 B , the I/O interface  114  can be covered and sealed by a removable door  115  of the image capture device  100 . The removable door  115  can be secured, for example, using a latch mechanism  115   a  (e.g., hidden as indicated using dotted lines) that is opened by engaging the associated button  110  as shown. 
     The removable door  115  can also be secured to the image capture device  100  using a hinge mechanism  115   b , allowing the removable door  115  to pivot between an open position allowing access to the I/O interface  114  and a closed position blocking access to the I/O interface  114 . The removable door  115  can also have a removed position (not shown) where the entire removable door  115  is separated from the image capture device  100 , that is, where both the latch mechanism  115   a  and the hinge mechanism  115   b  allow the removable door  115  to be removed from the image capture device  100 . 
     The image capture device  100  may also include a speaker  116  integrated into the body  102  or housing. The front surface of the image capture device  100  may include two drainage ports as part of a drainage channel  118 . The image capture device  100  may include an interactive display  120  that allows for interaction with the image capture device  100  while simultaneously displaying information on a surface of the image capture device  100 . As illustrated, the image capture device  100  may include the lens  104  that is configured to receive light incident upon the lens  104  and to direct received light onto an image sensor internal to the lens  104 . 
     The image capture device  100  of  FIGS.  1 A-D  includes an exterior that encompasses and protects internal electronics. In the present example, the exterior includes six surfaces (i.e. a front face, a left face, a right face, a back face, a top face, and a bottom face) that form a rectangular cuboid. Furthermore, both the front and rear surfaces of the image capture device  100  are rectangular. In other embodiments, the exterior may have a different shape. The image capture device  100  may be made of a rigid material such as plastic, aluminum, steel, or fiberglass. The image capture device  100  may include features other than those described here. For example, the image capture device  100  may include additional buttons or different interface features, such as interchangeable lenses, cold shoes and hot shoes that can add functional features to the image capture device  100 , etc. 
     The image capture device  100  may include various types of image sensors, such as a charge-coupled device (CCD) sensors, active pixel sensors (APS), complementary metal-oxide-semiconductor (CMOS) sensors, N-type metal-oxide-semiconductor (NMOS) sensors, and/or any other image sensor or combination of image sensors. 
     Although not illustrated, in various embodiments, the image capture device  100  may include other additional electrical components (e.g., an image processor, camera SoC (system-on-chip), etc.), which may be included on one or more circuit boards within the body  102  of the image capture device  100 . 
     The image capture device  100  may interface with or communicate with an external device, such as an external user interface device, via a wired or wireless computing communication link (e.g., the I/O interface  114 ). The user interface device may, for example, be the personal computing device  360  described below with respect to  FIG.  3 B . Any number of computing communication links may be used. The computing communication link may be a direct computing communication link or an indirect computing communication link, such as a link including another device or a network, such as the internet, may be used. 
     In some implementations, the computing communication link may be a Wi-Fi link, an infrared link, a Bluetooth (BT) link, a cellular link, a ZigBee link, a near field communications (NFC) link, such as an ISO/IEC 20643 protocol link, an Advanced Network Technology interoperability (ANT+) link, and/or any other wireless communications link or combination of links. 
     In some implementations, the computing communication link may be an HDMI link, a USB link, a digital video interface link, a display port interface link, such as a Video Electronics Standards Association (VESA) digital display interface link, an Ethernet link, a Thunderbolt link, and/or other wired computing communication link. 
     The image capture device  100  may transmit images, such as panoramic images, or portions thereof, to the user interface device (not shown) via the computing communication link, and the user interface device may store, process, display, or a combination thereof the panoramic images. 
     The user interface device may be a computing device, such as a smartphone, a tablet computer, a phablet, a smart watch, a portable computer, and/or another device or combination of devices configured to receive user input, communicate information with the image capture device  100  via the computing communication link, or receive user input and communicate information with the image capture device  100  via the computing communication link. 
     The user interface device may display, or otherwise present, content, such as images or video, acquired by the image capture device  100 . For example, a display of the user interface device may be a viewport into the three-dimensional space represented by the panoramic images or video captured or created by the image capture device  100 . 
     The user interface device may communicate information, such as metadata, to the image capture device  100 . For example, the user interface device may send orientation information of the user interface device with respect to a defined coordinate system to the image capture device  100 , such that the image capture device  100  may determine an orientation of the user interface device relative to the image capture device  100 . 
     Based on the determined orientation, the image capture device  100  may identify a portion of the panoramic images or video captured by the image capture device  100  for the image capture device  100  to send to the user interface device for presentation as the viewport. In some implementations, based on the determined orientation, the image capture device  100  may determine the location of the user interface device and/or the dimensions for viewing of a portion of the panoramic images or video. 
     The user interface device may implement or execute one or more applications to manage or control the image capture device  100 . For example, the user interface device may include an application for controlling camera configuration, video acquisition, video display, or any other configurable or controllable aspect of the image capture device  100 . 
     The user interface device, such as via an application, may generate and share, such as via a cloud-based or social media service, one or more images, or short video clips, such as in response to user input. In some implementations, the user interface device, such as via an application, may remotely control the image capture device  100  such as in response to user input. 
     The user interface device, such as via an application, may display unprocessed or minimally processed images or video captured by the image capture device  100  contemporaneously with capturing the images or video by the image capture device  100 , such as for shot framing, which may be referred to herein as a live preview, and which may be performed in response to user input. In some implementations, the user interface device, such as via an application, may mark one or more key moments contemporaneously with capturing the images or video by the image capture device  100 , such as with a tag, such as in response to user input. 
     The user interface device, such as via an application, may display, or otherwise present, marks or tags associated with images or video, such as in response to user input. For example, marks may be presented in a camera roll application for location review and/or playback of video highlights. 
     The user interface device, such as via an application, may wirelessly control camera software, hardware, or both. For example, the user interface device may include a web-based graphical interface accessible by a user for selecting a live or previously recorded video stream from the image capture device  100  for display on the user interface device. 
     The user interface device may receive information indicating a user setting, such as an image resolution setting (e.g., 3840 pixels by 2160 pixels), a frame rate setting (e.g., 60 frames per second (fps)), a location setting, and/or a context setting, which may indicate an activity, such as mountain biking, in response to user input, and may communicate the settings, or related information, to the image capture device  100 . 
       FIGS.  2 A-B  illustrate another example of an image capture device  200 . The image capture device  200  includes a body  202  and two camera lenses  204 ,  206  disposed on opposing surfaces of the body  202 , for example, in a back-to-back or Janus configuration. 
     The image capture device may include electronics (e.g., imaging electronics, power electronics, etc.) internal to the body  202  for capturing images via the lenses  204 ,  206  and/or performing other functions. The image capture device may include various indicators such as an LED light  212  and an LCD display  214 . 
     The image capture device  200  may include various input mechanisms such as buttons, switches, and touchscreen mechanisms. For example, the image capture device  200  may include buttons  216  configured to allow a user of the image capture device  200  to interact with the image capture device  200 , to turn the image capture device  200  on, and to otherwise configure the operating mode of the image capture device  200 . In an implementation, the image capture device  200  includes a shutter button and a mode button. It should be appreciated, however, that, in alternate embodiments, the image capture device  200  may include additional buttons to support and/or control additional functionality. 
     The image capture device  200  may also include one or more microphones  218 A and  218 B configured to receive and record audio signals (e.g., voice or other audio commands) in conjunction with recording video. 
     The image capture device  200  may include an I/O interface  220  and an interactive display  222  that allows for interaction with the image capture device  200  while simultaneously displaying information on a surface of the image capture device  200 . 
     The image capture device  200  may be made of a rigid material such as plastic, aluminum, steel, or fiberglass. In some embodiments, the image capture device  200  described herein includes features other than those described. For example, instead of the I/O interface  220  and the interactive display  222 , the image capture device  200  may include additional interfaces or different interface features. For example, the image capture device  200  may include additional buttons or different interface features, such as interchangeable lenses, cold shoes and hot shoes that can add functional features to the image capture device  200 , etc. 
       FIG.  2 C  is a cross-sectional view of the image capture device  200  of  FIGS.  2 A-B . The image capture device  200  is configured to capture spherical images, and accordingly, includes a first image capture device  224  and a second image capture device  226 . The first image capture device  224  defines a first field-of-view  228  as shown in  FIG.  2 C  and includes the lens  204  that receives and directs light onto a first image sensor  230 . 
     Similarly, the second image capture device  226  defines a second field-of-view  232  as shown in  FIG.  2 C  and includes the lens  206  that receives and directs light onto a second image sensor  234 . To facilitate the capture of spherical images, the image capture devices  224 ,  226  (and related components) may be arranged in a back-to-back (Janus) configuration such that the lenses  204 ,  206  face in generally opposite directions. 
     The fields-of-view  228 ,  232  of the lenses  204 ,  206  are shown above and below boundaries  236 ,  238 , respectively. Behind the first lens  204 , the first image sensor  230  may capture a first hyper-hemispherical image plane from light entering the first lens  204 , and behind the second lens  206 , the second image sensor  234  may capture a second hyper-hemispherical image plane from light entering the second lens  206 . 
     One or more areas, such as blind spots  240 ,  242  may be outside of the fields-of-view  228 ,  232  of the lenses  204 ,  206  so as to define a “dead zone.” In the dead zone, light may be obscured from the lenses  204 ,  206  and the corresponding image sensors  230 ,  234 , and content in the blind spots  240 ,  242  may be omitted from capture. In some implementations, the image capture devices  224 ,  226  may be configured to minimize the blind spots  240 ,  242 . 
     The fields-of-view  228 ,  232  may overlap. Stitch points  244 ,  246 , proximal to the image capture device  200 , at which the fields-of-view  228 ,  232  overlap may be referred to herein as overlap points or stitch points. Content captured by the respective lenses  204 ,  206 , distal to the stitch points  244 ,  246 , may overlap. 
     Images contemporaneously captured by the respective image sensors  230 ,  234  may be combined to form a combined image. Combining the respective images may include correlating the overlapping regions captured by the respective image sensors  230 ,  234 , aligning the captured fields-of-view  228 ,  232 , and stitching the images together to form a cohesive combined image. 
     A slight change in the alignment, such as position and/or tilt, of the lenses  204 ,  206 , the image sensors  230 ,  234 , or both, may change the relative positions of their respective fields-of-view  228 ,  232  and the locations of the stitch points  244 ,  246 . A change in alignment may affect the size of the blind spots  240 ,  242 , which may include changing the size of the blind spots  240 ,  242  unequally. 
     Incomplete or inaccurate information indicating the alignment of the image capture devices  224 ,  226 , such as the locations of the stitch points  244 ,  246 , may decrease the accuracy, efficiency, or both of generating a combined image. In some implementations, the image capture device  200  may maintain information indicating the location and orientation of the lenses  204 ,  206  and the image sensors  230 ,  234  such that the fields-of-view  228 ,  232 , stitch points  244 ,  246 , or both may be accurately determined, which may improve the accuracy, efficiency, or both of generating a combined image. 
     The lenses  204 ,  206  may be laterally offset from each other, may be off-center from a central axis of the image capture device  200 , or may be laterally offset and off-center from the central axis. As compared to image capture devices with back-to-back lenses, such as lenses aligned along the same axis, image capture devices including laterally offset lenses may include substantially reduced thickness relative to the lengths of the lens barrels securing the lenses. For example, the overall thickness of the image capture device  200  may be close to the length of a single lens barrel as opposed to twice the length of a single lens barrel as in a back-to-back configuration. Reducing the lateral distance between the lenses  204 ,  206  may improve the overlap in the fields-of-view  228 ,  232 . 
     Images or frames captured by the image capture devices  224 ,  226  may be combined, merged, or stitched together to produce a combined image, such as a spherical or panoramic image, which may be an equirectangular planar image. In some implementations, generating a combined image may include three-dimensional, or spatiotemporal, noise reduction (3DNR). In some implementations, pixels along the stitch boundary may be matched accurately to minimize boundary discontinuities. 
       FIGS.  3 A-B  are block diagrams of examples of image capture systems. Referring first to  FIG.  3 A , an image capture system  300  is shown. The image capture system  300  includes an image capture device  310  (e.g., a camera or a drone), which may, for example, be the image capture device  100  shown in  FIGS.  1 A-D  or the image capture device  200  shown in  FIGS.  2 A-B . 
     The image capture device  310  includes a processing apparatus  312  that is configured to receive a first image from the first image sensor  314  and receive a second image from the second image sensor  316 . The processing apparatus  312  may be configured to perform image signal processing (e.g., filtering, tone mapping, stitching, and/or encoding) to generate output images based on image data from the image sensor  314 , image sensor  316 , or both. The image capture device  310  includes a communications interface  318  for transferring images to other devices. The image capture device  310  includes a user interface  320  to allow a user to control image capture functions and/or view images. The image capture device  310  includes a battery  322  for powering the image capture device  310 . The components of the image capture device  310  may communicate with each other via the bus  324 . 
     The processing apparatus  312  may include one or more processors having single or multiple processing cores. The processing apparatus  312  may include memory, such as a random-access memory device (RAM), flash memory, or another suitable type of storage device such as a non-transitory computer-readable memory. The memory of the processing apparatus  312  may include executable instructions and data that can be accessed by one or more processors of the processing apparatus  312 . For example, the processing apparatus  312  may include one or more dynamic random access memory (DRAM) modules, such as double data rate synchronous dynamic random-access memory (DDR SDRAM). In some implementations, the processing apparatus  312  may include a digital signal processor (DSP). In some implementations, the processing apparatus  312  may include an application specific integrated circuit (ASIC). For example, the processing apparatus  312  may include a custom image signal processor. 
     The first image sensor  314  and the second image sensor  316  may be configured to detect light of a certain spectrum (e.g., the visible spectrum or the infrared spectrum) and convey information constituting an image as electrical signals (e.g., analog or digital signals). For example, the image sensors  314  and  316  may include CCDs or active pixel sensors in a CMOS. The image sensors  314  and  316  may detect light incident through a respective lens (e.g., a fisheye lens). In some implementations, the image sensors  314  and  316  include digital-to-analog converters. In some implementations, the image sensors  314  and  316  are held in a fixed orientation with respective fields of view that overlap. 
     The communications interface  318  may enable communications with a personal computing device (e.g., a smartphone, a tablet, a laptop computer, or a desktop computer). For example, the communications interface  318  may be used to receive commands controlling image capture and processing in the image capture device  310 . For example, the communications interface  318  may be used to transfer image data to a personal computing device. For example, the communications interface  318  may include a wired interface, such as a high-definition multimedia interface (HDMI), a universal serial bus (USB) interface, or a FireWire interface. For example, the communications interface  318  may include a wireless interface, such as a Bluetooth interface, a ZigBee interface, and/or a Wi-Fi interface. 
     The user interface  320  may include an LCD display for presenting images and/or messages to a user. For example, the user interface  320  may include a button or switch enabling a person to manually turn the image capture device  310  on and off. For example, the user interface  320  may include a shutter button for snapping pictures. 
     The battery  322  may power the image capture device  310  and/or its peripherals. For example, the battery  322  may be charged wirelessly or through a micro-USB interface. 
     The image capture system  300  may implement some or all of the techniques described in this disclosure, such as the method  800  described in  FIG.  8   . 
     Referring next to  FIG.  3 B , another image capture system  330  is shown. The image capture system  330  includes an image capture device  340  and a personal computing device  360  that communicate via a communications link  350 . The image capture device  340  may, for example, be the image capture device  100  shown in  FIGS.  1 A-D  or the image capture device  200  shown in  FIGS.  2 A-C . The personal computing device  360  may, for example, be the user interface device described with respect to  FIGS.  1 A-D . 
     The image capture device  340  includes a first image sensor  342  and a second image sensor  344  that are configured to capture respective images. The image capture device  340  includes a communications interface  346  configured to transfer images via the communication link  350  to the personal computing device  360 . 
     The personal computing device  360  includes a processing apparatus  362  that is configured to receive, using the communications interface  366 , a first image from the first image sensor  342  and a second image from the second image sensor  344 . The processing apparatus  362  may be configured to perform image signal processing (e.g., filtering, tone mapping, stitching, and/or encoding) to generate output images based on image data from the image sensors  342 ,  344 . 
     The first image sensor  342  and the second image sensor  344  are configured to detect light of a certain spectrum (e.g., the visible spectrum or the infrared spectrum) and convey information constituting an image as electrical signals (e.g., analog or digital signals). For example, the image sensors  342  and  344  may include CCDs or active pixel sensors in a CMOS. The image sensors  342  and  344  may detect light incident through a respective lens (e.g., a fisheye lens). In some implementations, the image sensors  342  and  344  include digital-to-analog converters. In some implementations, the image sensors  342  and  344  are held in a fixed relative orientation with respective fields of view that overlap. Image signals from the image sensors  342  and  344  may be passed to other components of the image capture device  340  via a bus  348 . 
     The communications link  350  may be a wired communications link or a wireless communications link. The communications interface  346  and the communications interface  366  may enable communications over the communications link  350 . For example, the communications interface  346  and the communications interface  366  may include an HDMI port or other interface, a USB port or other interface, a FireWire interface, a Bluetooth interface, a ZigBee interface, and/or a Wi-Fi interface. For example, the communications interface  346  and the communications interface  366  may be used to transfer image data from the image capture device  340  to the personal computing device  360  for image signal processing (e.g., filtering, tone mapping, stitching, and/or encoding) to generate output images based on image data from the image sensors  342  and  344 . 
     The processing apparatus  362  may include one or more processors having single or multiple processing cores. The processing apparatus  362  may include memory, such as RAM, flash memory, or another suitable type of storage device such as a non-transitory computer-readable memory. The memory of the processing apparatus  362  may include executable instructions and data that can be accessed by one or more processors of the processing apparatus  362 . For example, the processing apparatus  362  may include one or more DRAM modules, such as DDR SDRAM. 
     In some implementations, the processing apparatus  362  may include a DSP. In some implementations, the processing apparatus  362  may include an integrated circuit, for example, an ASIC. For example, the processing apparatus  362  may include a custom image signal processor. The processing apparatus  362  may exchange data (e.g., image data) with other components of the personal computing device  360  via a bus  368 . 
     The personal computing device  360  may include a user interface  364 . For example, the user interface  364  may include a touchscreen display for presenting images and/or messages to a user and receiving commands from a user. For example, the user interface  364  may include a button or switch enabling a person to manually turn the personal computing device  360  on and off. In some implementations, commands (e.g., start recording video, stop recording video, or snap photograph) received via the user interface  364  may be passed on to the image capture device  340  via the communications link  350 . 
     The image capture device  340  and/or the personal computing device  360  may be used to implement some or all of the techniques described in this disclosure, such as the method  800  of  FIG.  8   . 
       FIG.  4 A  is a diagram of a top-view of an image capture device  400  in accordance with embodiments of this disclosure. The image capture device  400  comprises a camera body  402  having two camera lenses  404 ,  406  structured on front and back surfaces  403 ,  405  of the camera body  402 . The two lenses  404 ,  406  are oriented in opposite directions and couple with two images sensors mounted on circuit boards (not shown). Other electrical camera components (e.g., an image processor, camera SoC (system-on-chip), etc.) may also be included on one or more circuit boards within the camera body  402  of the image capture device  400 . 
     The lenses  404 ,  406  may be laterally offset from each other, may be off-center from a central axis of the image capture device  400 , or may be laterally offset and off-center from the central axis. As compared to an image capture device with back-to-back lenses, such as lenses aligned along the same axis, the image capture device  400  including laterally offset lenses  404 ,  406  may include substantially reduced thickness relative to the lengths of the lens barrels securing the lenses  404 ,  406 . For example, the overall thickness of the image capture device  400  may be close to the length of a single lens barrel as opposed to twice the length of a single lens barrel as in a back-to-back configuration. 
     The image capture device  400  includes a microphone array that comprises a front-facing component  408 , a rear-facing component  412 , and a side-facing component  418 . The front-facing component  408 , the rear-facing component  412 , and the side-facing component  418  may each be referred to as a microphone assembly. The side-facing component  418  may be on any side of the image capture device  400  that is perpendicular to the front-facing component  408  and the rear-facing component  412 , and may include a top surface, a bottom surface, a left surface, a right surface, or any combination thereof. As shown in  FIG.  4 A , the front-facing component  408  is disposed on the front surface  403  of the image capture device. The front-facing component  408  may include one or more microphone elements  414 . The microphone elements  414  may be configured such that they are distanced approximately 6 mm to 18 mm apart. The rear-facing component  412  is disposed on the back surface  405  of the image capture device  400 . The rear-facing component  412  may include one or more microphone elements  416 . One or more of the microphone elements  416  may be configured as a drain microphone. The side-facing component  418  is shown on a top surface  420  of the image capture device  400  in this example. The side-facing component  418  may include one or more microphone elements  422 . The microphone elements  422  may be configured such that they are distanced approximately 6 mm to 18 mm apart. The 6 mm to 18 mm spacing may determine the frequency resolution of the output. For example, the larger the spacing, the lower the highest resolvable frequency. The spacing may be adjusted depending on the resolution required. 
     The front-facing component  408 , microphone elements  414 , rear-facing component  412 , and microphone elements  416  are shown in broken lines as they may not be visible in this view. The front-facing component  408 , rear-facing component  412 , and side-facing component  418  of the microphone array may represent microphone elements on an X, Y, Z axis to create X, Y, Z components of a First Order Ambisonics B-Format, as shown in  FIG.  5   . These microphone elements may be oriented on a sphere or off-axis, and may be transformed to the First Order Ambisonics B-Format. 
       FIG.  4 B  is a diagram of a front-view of the image capture device  400  shown in  FIG.  4 A  in accordance with embodiments of this disclosure. As shown in  FIG.  4 B , the front surface  403  of the image capture device  400  comprises the camera lens  404  and the front-facing component  408 . Although the front-facing component  408  may include any number of microphone elements, the example shown in  FIG.  4 B  includes three microphone elements  414 . Each of the microphone elements  414  may be configured such that they are distanced approximately 6 mm to 18 mm apart. The side-facing component  418  and the microphone elements  422  are shown in broken lines as they may not be visible in this view. 
       FIG.  4 C  is a diagram of a rear-view of the image capture device  400  shown in  FIG.  4 A  in accordance with embodiments of this disclosure. As shown in  FIG.  4 C , the back surface  405  of the image capture device  400  comprises the camera lens  406  and the rear-facing component  412 . In an example, the back surface  405  of the image capture device  400  may include an interactive display  430  that allows for interaction with the image capture device  400  while simultaneously displaying information on a surface of the image capture device  400 . Although the rear-facing component  412  may include any number of microphone elements, the example shown in  FIG.  4 C  includes one microphone element  416 . In an example, one or more of the microphone elements  416  may be configured as a drain microphone. The side-facing component  418  and the microphone elements  422  are shown in broken lines as they may not be visible in this view. 
       FIG.  5    is a flow diagram of an example of a method  500  for reducing vibration noise. The method  500  may be implemented by an image capture device, for example image capture device  100  shown in  FIGS.  1 A- 1 D , image capture device  400  shown in  FIGS.  4 A- 4 C , or both. As shown in  FIG.  5   , the method  500  includes obtaining  510  a microphone signal. The microphone signal may include an acoustic signal portion, a mechanical noise portion, or both. The mechanical noise portion may include unwanted or undesired noise introduced into the microphone signal caused by structural vibrations that are detected by one or more microphones via the image capture device body. 
     The method  500  includes obtaining  520  a vibration signal. The vibration signal may be obtained using any vibration sensor such as a piezoelectric vibration sensor or an inertial measurement unit (IMU). Although any vibration sensor may be used, the examples described herein refer to the vibration sensor as an IMU for simplicity. The IMU may include one or more components such as an accelerometer, a gyroscope, a magnetometer, or any combination thereof. Each component of the IMU may detect structural vibration and generate one or more vibration signals. The one or more vibration signals may include respective signals associated with an X-axis, Y-axis, Z-axis, or any combination thereof, for each component of the IMU. 
     Typical sampling rates for vibration sensors are insufficient for noise detection in the audible bandwidth. For example, a typical sampling rate for an accelerometer is 200 Hz. In the embodiments disclosed herein, the sampling rates for the vibration sensors are set to overlap with the human audible spectrum of about 20 Hz to about 20 kHz. For example, an accelerometer sampling rate may be set to about 1.6 kHz and a gyroscope sampling rate may be set to about 6.4 kHz. 
     As shown in  FIG.  5   , the method  500  includes upsampling  530  the vibration signal. Since the vibration signal is obtained as a lower sampling rate than the microphone signal, the vibration signal is upsampled  530  to match the sampling rate of the microphone signal. 
     The method  500  includes determining  540  a correlation value. The correlation value may be based on the microphone signal and the upsampled vibration signal. A correlation value may be determined between each microphone and each axis of each component of the IMU. For example, a device that includes three microphones, an accelerometer, and a gyroscope, 18 correlation values may be determined. The correlation values may range from 0 to 1, where a value of 0 would indicate no correlation between a microphone signal and a respective vibration signal, and a value of 1 would indicate a high correlation between the microphone signal and the respective vibration signal. An example of the correlation between microphone signals and vibration signals is shown in  FIG.  8   . 
     Referring again to  FIG.  5   , in some examples, the method  500  may include determining  550  whether a correlation value is above a threshold. In some examples, the threshold for the correlation value may be 0.5. If the correlation value is determined to be above the threshold, the method includes determining  560  one or more filter coefficients. The filter coefficients may be based on the upsampled vibration signal. 
     The method  500  includes filtering  570  the upsampled vibration signal based on the filter coefficients to remove the mechanical noise portion of the microphone signal to obtain a processed microphone signal. In some examples, the filter coefficient may be applied to the most correlated axis per microphone. For example, if a microphone signal has a correlation value of 1 associated with an X-axis accelerometer signal, a correlation value of 0.1 associated with a Y-axis accelerometer signal, and a correlation value of 0.4 associated with a Z-axis accelerometer signal, the filter coefficient may be applied to the microphone signal associated with the X-axis accelerometer signal. In some examples, the vibration signal may be a composite signal including the X-axis, Y-axis, and Z-axis components associated with the vibration signal. 
     The method  500  includes outputting  580  the processed microphone signal. Outputting  580  the processed microphone signal may include transmitting the processed microphone signal. Outputting  580  the processed microphone signal may include storing the microphone signal, for example in a memory such as processing apparatus  312  of  FIG.  3 A . 
       FIG.  6   . is a flow diagram of another example of a method  600  for reducing vibration noise in microphone signals. The method  600  may be implemented by an image capture device, for example image capture device  100  shown in  FIGS.  1 A- 1 D , image capture device  400  shown in  FIGS.  4 A- 4 C , or both. As shown in  FIG.  6   , the method  600  includes obtaining  610  a first microphone signal and obtaining  615  a second microphone signal. The microphone signals may each include an acoustic signal portion, a mechanical noise portion, or both. The mechanical noise portion may include unwanted or undesired noise introduced into the microphone signal caused by structural vibrations that are detected by one or more microphones via the image capture device body. 
     The method  600  includes obtaining  620  a vibration signal. The vibration signal may be obtained using any vibration sensor such as a piezoelectric vibration sensor or an IMU. Although any vibration sensor may be used, the examples described herein refer to the vibration sensor as an IMU for simplicity. The IMU may include one or more components such as an accelerometer, a gyroscope, a magnetometer, or any combination thereof. Each component of the IMU may detect structural vibration and generate one or more vibration signals. The one or more vibration signals may include respective signals associated with an X-axis, Y-axis, Z-axis, or any combination thereof, for each component of the IMU. 
     Typical sampling rates for vibration sensors are insufficient for noise detection in the audible bandwidth. For example, a typical sampling rate for an accelerometer is 200 Hz. In the embodiments disclosed herein, the sampling rates for the vibration sensors are set to overlap with the human audible spectrum of about 20 Hz to about 20 kHz. For example, an accelerometer sampling rate may be set to about 1.6 kHz and a gyroscope sampling rate may be set to about 6.4 kHz. 
     As shown in  FIG.  6   , the method  600  includes upsampling  630  the vibration signal. Since the vibration signal is obtained as a lower sampling rate than the microphone signals, the vibration signal is upsampled  630  to match the sampling rate of the microphone signals. 
     The method  600  includes determining  640  a correlation value. The correlation value may be based on the first microphone signal, the second microphone signal, and the upsampled vibration signal. A correlation value may be determined between each microphone and each axis of each component of the IMU. For example, a device that includes three microphones, an accelerometer, and a gyroscope, 18 correlation values may be determined. The correlation values may range from 0 to 1, where a value of 0 would indicate no correlation between a microphone signal and a respective vibration signal, and a value of 1 would indicate a high correlation between the microphone signal and the respective vibration signal. An example of the correlation between microphone signals and vibration signals is shown in  FIG.  8   . 
     Referring again to  FIG.  6   , in some examples, the method  600  may include determining  650  whether a correlation value is above a threshold. In some examples, the threshold for the correlation value may be 0.5. If the correlation value is determined to be above the threshold, the method includes determining  660  one or more filter coefficients. The filter coefficients may be based on the upsampled vibration signal. 
     The method  600  includes filtering  670  the upsampled vibration signal based on the filter coefficients to remove the mechanical noise portion of the microphone signal to obtain one or more processed microphone signals. In some examples, the filter coefficient may be applied to the most correlated axis per microphone. For example, if a microphone signal has a correlation value of 1 associated with an X-axis accelerometer signal, a correlation value of 0.1 associated with a Y-axis accelerometer signal, and a correlation value of 0.4 associated with a Z-axis accelerometer signal, the filter coefficient may be applied to the microphone signal associated with the X-axis accelerometer signal. 
     The method  600  includes outputting  680  the processed microphone signals. Outputting  680  the processed microphone signals may include transmitting the processed microphone signals. Outputting  680  the processed microphone signals may include storing the microphone signals, for example in a memory such as processing apparatus  312  of  FIG.  3 A . 
       FIG.  7    is a block diagram of an example of an integrated circuit  700  for reducing vibration noise. The integrated circuit  700  may be implemented in an image capture device, for example image capture device  100  shown in  FIGS.  1 A- 1 D , image capture device  400  shown in  FIGS.  4 A- 4 C , or both. As shown in  FIG.  7   , the integrated circuit  700  includes a microphone  710 , a vibration sensor  720 , an upsampler  730 , a filter adapter  740 , a filter  750 , and a summing unit  755 . The summing unit  755  may be configured to perform an addition operation, a subtraction operation, or both. The integrated circuit  700  is shown with one microphone and one vibration sensor for simplicity and clarity, and it is understood that some implementations may include multiple microphones, multiple vibration sensors, or both. In some implementations, the microphone  710 , the vibration sensor  720 , or both may be separate from the integrated circuit  700 . 
     As shown in  FIG.  7   , the microphone  710  is configured to receive a desired acoustical input  760  from an acoustic source  765  and undesired mechanical noise  770 . The undesired mechanical noise  770  may be caused by a vibration  775 . The undesired mechanical noise  770  may be caused by a structural vibration  775  that may be detected by the microphone  710  via the image capture device body. The undesired mechanical noise  770  may introduce noise into the microphone signal  780 . 
     The vibration sensor  720  is configured to detect the structural vibration  775 . The vibration sensor  720  is configured to receive a vibration input  777  caused by the structural vibration  775 . The vibration sensor may include a piezoelectric vibration sensor or an IMU. The IMU may include one or more components such as an accelerometer, a gyroscope, a magnetometer, or any combination thereof. Each component of the IMU may detect structural vibration and generate one or more vibration signals. The one or more vibration signals may include respective signals associated with an X-axis, Y-axis, Z-axis, or any combination thereof, for each component of the IMU. 
     The upsampler  730  is configured to receive the vibration signal  785  from the vibration sensor  720 . The upsampler  730  is configured to upsample the vibration signal  785 . Since the vibration signal  785  may be obtained at a lower sampling rate than the microphone signal  780 , the upsampler  730  is configured to upsample the vibration signal  785  to match the sampling rate of the microphone signal  780  and output an upsampled vibration signal  787 . 
     The filter adapter  740  is configured to receive the microphone signal  780  and the upsampled vibration signal  787 . The filter adapter is configured to apply an adaptive algorithm to the microphone signal  780  and the upsampled vibration signal  787  to minimize the difference between the two signals. An example adaptive algorithm may include a normalized least mean square algorithm. The normalized least mean square algorithm may be configured to mimic a desired filter by determining the filter coefficients that relate to producing the least mean square of an error signal. The error signal in this example is the difference between the desired signal and the actual signal. The output of the filter adapter  740  is used to update the filter  750 . The filter coefficients of filter  750  may be adjusted based on the least mean square result of the upsampled vibration signal and the microphone signal. 
     The filter  750  is configured to receive the upsampled vibration signal  787 . The filter  750  is configured to filter the upsampled vibration signal  787  to obtain the filtered vibration signal  790 . The summing unit  755  is configured to remove the filtered vibration signal  790  from the microphone signal  780  using a subtraction operation and output the error signal  795 . The error signal  795  may be input to the filter adapter  740  to form a feedback loop to continuously update the filter  750 . In this example, the error signal  795  is the desired signal, i.e. the microphone signal without vibration noise. 
       FIG.  8    is a diagram of example plots of correlation values  800  of microphone and IMU signals. In this example, accelerometer-microphone cross-correlation plots  810  and gyroscope-microphone cross-correlation plots  820  for a device configured with three microphones (MIC1, MIC2, MIC 3) are shown. The accelerometer-microphone cross-correlation plots  810  show the correlation between the signals of each of MIC 1, MIC 2, and MIC 3 and the accelerometer signals for each of X-axis, Y-axis, and Z-axis of the accelerometer. The accelerometer-microphone cross-correlation plots  810  also show the sum of the signals of each accelerometer axis for each microphone. The gyroscope-microphone cross-correlation plots  820  show the correlation between the signals of each of MIC 1, MIC 2, and MIC 3 and the gyroscope signals for each of X-axis, Y-axis, and Z-axis of the gyroscope. The gyroscope-microphone cross-correlation plots  820  also show the sum of the signals of each gyroscope axis for each microphone. 
     As shown in  FIG.  8   , the correlation values may range from -1 to 1, where a value of 0 indicates no correlation between a microphone signal and a respective vibration signal, a value of 1 indicates a perfect correlation between the microphone signal and the respective vibration signal, and a value of -1 indicates an inverse correlation or negative correlation between the microphone signal and the respective vibration signal. As shown in  FIG.  8   , graph A is a representation of the cross-correlation between the MIC 2 signal and the X-axis accelerometer signal. In graph A, the microphone signal of MIC 2 is shown to have a correlation value of 1 associated with an X-axis accelerometer signal. Graph B is a representation of the cross-correlation between the MIC 2 signal and the Z-axis gyroscope signal. In graph B, the microphone signal of MIC 2 has a correlation value of about 0.1 associated with a Z-axis gyroscope signal. As shown in  FIG.  8   , the cross-correlations for each microphone signal stream may be summed to obtain a composite microphone signal. For example, graph C is a representation of the summed microphone signal stream for MIC 1 that includes the X-axis, Y-axis, and Z-axis components associated with the accelerometer signal. 
     While the disclosure has been described in connection with certain embodiments, it is to be understood that the disclosure is not to be limited to the disclosed embodiments but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims, which scope is to be accorded the broadest interpretation so as to encompass all such modifications and equivalent structures as is permitted under the law.