Cascaded Image Processing for Noise Reduction

Abstract

The present disclosure provides systems, methods, and devices for image processing that support noise reduction in low light video sequences. Noise reduction is achieved through a set of cascaded operations that are configured based on each set of operation positions in the cascaded pipeline. The cascade can be implemented as a series of cascaded image post-processing engines (IPEs) in an image signal processor (ISP).

Description

[Technical Field]

[0001]

[0001] Aspects of the present disclosure relate generally to image processing, and more particularly to noise reduction in images. Several features can enable and provide improved image quality, including supporting real-time high-resolution video sequences in low-light environments. [Background technology]

[0002]

[0002] Image capture devices have inherent limitations. Image quality is related to the sensitivity of the image sensor that captures the image and the brightness of the scene being captured. Limitations on both the image sensor's capabilities and available light can impose limitations on capturing high-quality images. Summary of the Invention

[0003] The following summarizes some aspects of the present disclosure to provide a basic understanding of the discussed technology. This summary is not an extensive overview of all of the contemplated features of the present disclosure, and is not intended to identify key or critical elements of all aspects of the present disclosure or to delineate the scope of any or all aspects of the present disclosure. Its sole purpose is to present some concepts of one or more aspects of the present disclosure in summary form as a prelude to the more detailed description that is presented later.

[0004]

[0004] An image capture device is a device capable of capturing one or more digital images, whether still photographs or a sequence of images for video, and can be incorporated into a wide variety of devices. By way of example, an image capture device may include a standalone digital camera or digital video camcorder; a camera-equipped wireless communication device handset, such as a mobile phone, cellular phone, or satellite radiotelephone, a personal digital assistant (PDA), a panel or tablet, a gaming device, or the like; a computing device, such as a webcam, a video surveillance camera, or other device with digital imaging or video capabilities.

[0005] Generally, this disclosure describes image processing techniques for digital cameras having an image sensor and an image signal processor (ISP). The image signal processor can be configured to control the capture of image frames from one or more image sensors and process one or more image frames from the one or more image sensors to generate a view of a scene in a corrected image frame. The corrected image frame can be part of a series of image frames forming a video sequence. The video sequence can include other image frames received from the image sensor or other image sensors and / or other corrected image frames based on input from the image sensor or other image sensors.

[0006] In one embodiment, an image signal processor can receive instructions to capture a series of image frames in response to loading software, such as a camera application, on a CPU. The image signal processor can be configured to generate a single flow of output frames based on corresponding corrected images from the image sensor. This single flow of output frames can include image frames including image data from the image sensor that have been corrected, such as by processing through an image post-processing engine (IPE), a cascaded series of IPEs, and / or other image processing circuitry to perform one or more of noise reduction, gamma correction, and tone mapping. The corrected image frames can be generated by combining aspects of the image correction of the present disclosure with other computational photography techniques, such as high dynamic range (HDR) photography or multi-frame noise reduction (MFNR).

[0007] After an output frame representing a scene has been determined by the image signal processor using the image corrections described in various embodiments herein, the output frame can be displayed on a device display as a single still image and / or as part of a video sequence, saved to a storage device as a picture or video sequence, transmitted over a network, and / or printed to an output medium. For example, the image signal processor can be configured to obtain input frames of image data (e.g., pixel values) from various image sensors and then generate corresponding output frames of image data (e.g., preview display frames, still image capture, frames for video, etc.). In other examples, the image signal processor can output frames of image data to various output devices and / or camera modules for further processing, such as for 3A parameter synchronization (e.g., automatic focus (AF), automatic white balance (AWB), and automatic exposure control (AEC)), generating a video file via the output frames, composing frames for display, composing frames for storage, and transmitting frames over a network connection. That is, the image signal processor may acquire incoming frames from one or more image sensors, each coupled to one or more camera lenses, and then generate a flow of output frames to output to various destinations. In such an embodiment, the image signal processor may be configured to generate a flow of output frames that may have improved appearance in low-light photography.

[0008] In some aspects, the method can be performed for HDR photography, where a first image frame and a second image frame are captured using different exposure times, different apertures, different lenses, or other different characteristics, and when the two image frames are combined, this can result in an improved dynamic range of the fused image. In some aspects, the method can be performed for MFNR photography, where the first image frame and the second image frame are captured using the same exposure time or different exposure times.

[0009] In some aspects, the device may include an image signal processor or processors that include specific functions related to camera control and / or processing, such as enabling or disabling image correction or otherwise controlling aspects of image correction, such as by specifying matrices for tone mapping, amount of gamma correction, or color correction. The at least one processor may also, or alternatively, include an application processor. The methods and techniques described herein may be performed entirely by the image signal processor or processor, or various operations may be divided between the image signal processor and the processor, or in some aspects, across additional processors.

[0010] The apparatus may include one, two, or more image sensors, such as a first image sensor. When multiple image sensors are present, the first image sensor may have a larger field of view (FOV) than the second image sensor, or the first image sensor may have a different sensitivity or a different dynamic range than the second image sensor. In one example, the first image sensor may be a wide-angle image sensor and the second image sensor may be a telephoto image sensor. In another example, the first sensor is configured to acquire images through a first lens having a first optical axis, and the second sensor is configured to acquire images through a second lens having a second optical axis different from the first optical axis. Additionally or alternatively, the first lens may have a first magnification and the second lens may have a second magnification different from the first magnification. This configuration may occur using a lens cluster on the mobile device, such as when multiple image sensors and associated lenses are arranged at offset positions on the front or back of the mobile device. Additional image sensors with larger, smaller, or the same field of view may also be included. The image correction techniques described herein may be applied to image frames captured from any of the image sensors in a multi-sensor device.

[0011] In an additional aspect of the present disclosure, a device configured for image processing and / or image capture is disclosed. The device includes a means for capturing an image frame. The device further includes one or more means for capturing data representing a scene, such as an image sensor (including a charge-coupled device (CCD), a Bayer filter sensor, an infrared (IR) detector, an ultraviolet (UV) detector, a complimentary metal-oxide-semiconductor (CMOS) sensor), or a time-of-flight detector. The device may further include one or more means (including a simple lens, a compound lens, a spherical lens, and an aspherical lens) for integrating and / or focusing light rays into the one or more image sensors. These components can be controlled to capture a first image frame and / or a second image frame, which are input to the image processing techniques described herein.

[0012]

[0012] Other aspects, features, and implementations will become apparent to those skilled in the art upon reviewing the following description of certain exemplary aspects in conjunction with the accompanying figures. While features may be discussed in connection with certain aspects and figures below, various aspects may include one or more of the advantageous features discussed herein. In other words, while one or more aspects may be discussed as having certain advantageous features, one or more of such features may also be used in accordance with various aspects. Similarly, although exemplary aspects may be discussed below as device, system, or method aspects, the exemplary aspects may be implemented in various devices, systems, and methods.

[0013]

[0013] The method can be embodied in a computer-readable medium as computer program code including instructions that cause a processor to perform the steps of the method. In some embodiments, the processor can be part of a mobile device including a first network adapter configured to transmit data, such as images or video, as recorded data or streaming data over a first network connection of a plurality of network connections, a processor coupled to the first network adapter, and a memory. The processor can cause transmission of the corrected image frames described herein over a wireless communication network, such as a 5G NR communication network.

[0014]

[0014] The foregoing has outlined rather broadly the features and technical advantages of embodiments of the present disclosure in order that the following Detailed Description may be better understood. Additional features and advantages will be described hereinafter. The concepts and specific examples disclosed may be readily utilized as a basis for modifying or designing other structures for carrying out the same purposes of the present disclosure. Such equivalent constructions do not depart from the scope of the appended claims. The concepts disclosed herein, both their organization and method of operation, characteristic of the concepts disclosed herein, together with associated advantages, will be better understood by considering the following description in conjunction with the accompanying figures. Each of the figures is provided for purposes of illustration and description, and not as a definition of the limits of the claims.

[0015]

[0015] While aspects and implementations are described in this application by way of example for several embodiments, those skilled in the art will recognize that additional implementations and use cases may occur in many different configurations and scenarios. The innovations described herein may be implemented across many different platform types, devices, systems, shapes, sizes, and packaging configurations. For example, aspects and / or applications may occur via integrated chip implementations and other non-modular component-based devices (e.g., end-user devices, vehicles, communications devices, computing devices, industrial equipment, retail / purchasing devices, medical devices, artificial intelligence (AI)-enabled devices, etc.). While some embodiments may or may not be specifically targeted to a use case or application, a wide variety of combinations of applicability of the described innovations may arise. Implementations may range widely, from chip-level or modular components to non-modular, non-chip-level implementations, and even to centralized, distributed, or original equipment manufacturer (OEM) devices or systems incorporating one or more aspects of the described innovations. In some practical settings, devices incorporating the described aspects and features may also necessarily include additional components and features to implement and practice the claimed and described aspects. For example, transmitting and receiving wireless signals necessarily includes several components for analog and digital purposes (e.g., hardware components including antennas, radio frequency (RF) chains, power amplifiers, modulators, buffers, processors, interleavers, summers / analog summers, etc.). It is contemplated that the innovations described herein may be practiced in a wide variety of devices, chip-level components, systems, distributed configurations, end-user devices, etc., of various sizes, shapes, and configurations. [Brief explanation of the drawings]

[0016]

[0016] A further understanding of the nature and advantages of the present disclosure may be realized by reference to the following drawings. In the accompanying drawings, similar components or features may have the same reference numerals. Furthermore, various components of the same type may be distinguished by following the reference numeral with a dash and a second numeral that distinguishes between the similar components. When only a first reference numeral is used in this specification, the description is applicable to any one of the similar components having the same first reference numeral, regardless of the second reference numeral.

[0017] [Figure 1]

[0017] A block diagram of an exemplary device 100 for performing image capture from one or more image sensors is shown. [Figure 2]

[0018] FIG. 1 is a block diagram illustrating a cascaded image post-processing engine (IPE), according to one or more aspects. [Figure 3]

[0019] 1 is a flowchart illustrating a method for processing an image frame using multiple noise reduction operations, according to one or more aspects. [Figure 4]

[0020] FIG. 2 is a block diagram illustrating a processing flow for an image frame through cascaded image post-processing engines (IPEs), according to one or more aspects.

[0018]

[0021] Like reference numbers and designations in the various drawings indicate like elements. DETAILED DESCRIPTION OF THE INVENTION

[0019]

[0022] The detailed description set forth below in connection with the accompanying drawings is intended as an illustration of various configurations and is not intended to limit the scope of the present disclosure. Rather, the detailed description includes specific details intended to provide a thorough understanding of the inventive subject matter. Those skilled in the art will appreciate that these specific details are not required in every instance and that, in some instances, well-known structures and components are shown in block diagram form for clarity of presentation.

[0020]

[0023] The present disclosure provides systems, apparatus, methods, and computer-readable media that support high-quality, high-resolution (e.g., 4K, 8K, 16K, or higher) video capture using real-time processing to reduce noise, increase brightness, and improve detail and texture in the video. Aspects of the present disclosure may be particularly advantageous for image capture devices with small pixel sizes that have reduced light-gathering capabilities and are more likely to be adversely affected in low-light environments.

[0021]

[0024] Particular implementations of the subject matter described in this disclosure can be implemented to realize one or more of the following potential advantages or benefits: In some aspects, the present disclosure provides techniques for reducing noise, increasing brightness, enhancing image quality, improving detail and texture, and providing real-time processing of high-resolution video sequences.

[0022]

[0025] An exemplary device for capturing image frames using one or more image sensors, such as a smartphone, may include a two, three, four, or more camera configuration on the back (e.g., opposite the user display) or front (e.g., on the same side as the user display) of the device. A device with multiple image sensors includes one or more image signal processors (ISPs), computer vision processors (CVPs) (e.g., AI engines), or other suitable circuitry for processing images captured by the image sensors. The one or more image signal processors can provide processed image frames to memory and / or a processor (such as an application processor, an image front end (IFE), an image processing engine (IPE), or other suitable processing circuitry) for further processing, such as for encoding, storage, transmission, or other manipulation.

[0023]

[0026] As used herein, an image sensor may refer to the image sensor itself as well as any other components coupled to the image sensor that are used to generate image frames for processing by an image signal processor or other logic circuitry, or for storage in memory, whether a short-term buffer or longer-term non-volatile memory. For example, an image sensor may include other components of a camera, including a shutter, buffer, or other readout circuitry for accessing individual pixels of the image sensor. An image sensor may also refer to an analog front end or other circuitry for converting analog signals into a digital representation of the image frame that is provided to digital circuitry coupled to the image sensor.

[0024]

[0027] In the following description, numerous specific details are set forth, such as examples of specific components, circuits, and processes, to provide a thorough understanding of the present disclosure. The term "coupled," as used herein, means directly connected or connected via one or more intervening components or circuits. Also, in the following description, for purposes of explanation, specific terminology is set forth to provide a thorough understanding of the present disclosure. However, it will be apparent to those skilled in the art that these specific details may not be required to practice the teachings disclosed herein. In other instances, well-known circuits and devices are shown in block diagram form to avoid obscuring the teachings of the present disclosure.

[0025]

[0028] Some portions of the following Detailed Description are presented in terms of procedures, logic blocks, processing, and other symbolic representations of operations on data bits within a computer memory. In this disclosure, a procedure, logic block, process, etc., is conceived to be a self-consistent sequence of steps or instructions leading to a desired result. These steps require physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated in a computer system.

[0026]

[0029] In the figures, a single block may be described as performing one or more functions. The functions performed by the block may be performed in a single component, across multiple components, and / or may be implemented using hardware, software, or a combination of hardware and software. To clearly illustrate this interchangeability between hardware and software, various illustrative components, blocks, modules, circuits, and steps are described below generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the particular application and design constraints imposed on the overall system. Those skilled in the art may implement the described functionality in various ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure. Also, the illustrative device may include components other than those shown, including well-known components such as a processor, memory, etc.

[0027]

[0030] Aspects of the present disclosure are applicable to any suitable electronic device that includes or is coupled to two or more image sensors capable of capturing image frames (or "frames"). Moreover, aspects of the present disclosure can be implemented in devices having or coupled to image sensors of the same or different capabilities and characteristics (resolution, shutter speed, sensor type, etc.). Furthermore, aspects of the present disclosure can be implemented in devices for processing image frames, such as processing devices capable of retrieving stored images for processing, including processing devices present in cloud computing systems, regardless of whether the device includes or is coupled to an image sensor.

[0028]

[0031] Unless otherwise expressly stated, and as will be apparent from the discussion that follows, discussions throughout this application utilizing terms such as "accessing," "receiving," "sending," "using," "selecting," "determining," "normalizing," "multiplying," "averaging," "monitoring," "comparing," "applying," "updating," "measuring," "deriving," "solving," "generating," and the like, will be understood to refer to the actions and processes of a computer system or similar electronic computing device that manipulates data represented as physical (electronic) quantities in the computer system's registers and memory, and converts those data into other data that are similarly represented as physical quantities in the computer system's registers, memory, or other such information storage, transmission, or display device.

[0029]

[0032] The terms "device" and "apparatus" are not limited to one physical object or a particular number of physical objects (such as a smartphone, a camera controller, or a processing system). As used herein, a device can be any electronic device having one or more components capable of implementing at least some portions of the present disclosure. Although the following description and examples use the term "device" to describe various aspects of the present disclosure, the term "device" is not limited to a particular configuration, type, or number of objects. As used herein, an apparatus may include a device for performing the described operations, or a portion of such a device.

[0030]

[0033] 1 shows a block diagram of an exemplary device 100 for performing image capture from one or more image sensors. Device 100 may include, or be otherwise coupled to, an image signal processor 112 for processing image frames from one or more image sensors, such as first image sensor 101, second image sensor 102, and depth sensor 140. In some implementations, device 100 also includes, or is coupled to, a processor 104 and a memory 106 that stores instructions 108. Device 100 may also include, or be coupled to, a display 114 and input / output (I / O) components 116. I / O components 116, such as a touchscreen interface and / or physical buttons, can be used to interact with a user. I / O components 116 may also include network interfaces for communicating with other devices, including a wide area network (WAN) adapter 152, a local area network (LAN) adapter 153, and / or a personal area network (PAN) adapter 154. An exemplary WAN adapter is a 4G LTE or 5G NR wireless network adapter. An exemplary LAN adapter 153 is an IEEE 802.11 WiFi wireless network adapter. An exemplary PAN adapter 154 is a Bluetooth wireless network adapter. Each of adapters 152, 153, and / or 154 may be coupled to an antenna, including multiple antennas configured for primary reception and diversity reception and / or configured to receive a particular frequency band. Device 100 may further include or be coupled to a power source 118 for device 100, such as a battery or components for coupling device 100 to an energy source.Device 100 may also include or be coupled to additional features or components not shown in Figure 1. In one embodiment, a wireless interface, which may include a number of transceivers and a baseband processor, may be coupled to or included within WAN adapter 152 for the wireless communication device. In a further embodiment, an analog front end (AFE) for converting analog image frame data to digital image frame data may be coupled between image sensors 101 and 102 and image signal processor 112.

[0031]

[0034] The device may include or be coupled to a sensor hub 150 for interfacing with sensors to receive data regarding the movement of device 100, data regarding the environment surrounding device 100, and / or other non-camera sensor data. One exemplary non-camera sensor is a gyroscope, which is a device configured to measure rotation, orientation, and / or angular velocity to generate motion data. Another exemplary non-camera sensor is an accelerometer, which is a device configured to measure acceleration, which can also be used to determine speed and distance traveled by appropriately integrating the measured acceleration, and one or more of acceleration, speed, and / or distance can be included in the generated motion data. In some embodiments, a gyroscope in an electronic image stabilization system (EIS) can be coupled to the sensor hub or directly to image signal processor 112. In another example, the non-camera sensor can be a global positioning system (GPS) receiver.

[0032]

[0035] The image signal processor 112 can receive image data, such as that used to form the image frames. In one embodiment, a local bus connection couples the image signal processor 112 to the image sensor 101 of the first camera and the image sensor 102 of the second camera. In another embodiment, a wired interface couples the image signal processor 112 to an external image sensor. In a further embodiment, a wireless interface couples the image signal processor 112 to the image sensors 101, 102.

[0033]

[0036] The first camera may include a first image sensor 101 and a corresponding first lens 131. The second camera may include a second image sensor 102 and a corresponding second lens 132. Each of the lenses 131 and 132 may be controlled by an associated autofocus (AF) algorithm 133 running in the ISP 112, which adjusts the lenses 131 and 132 to focus on a particular focal plane at a particular scene depth from the image sensors 101 and 102. The AF algorithm 133 may be assisted by a depth sensor 140.

[0034]

[0037] The first image sensor 101 and the second image sensor 102 are configured to capture one or more image frames. The lenses 131 and 132 focus light onto the image sensors 101 and 102, respectively, through one or more apertures for receiving light, one or more shutters for blocking light outside of an exposure window, one or more color filter arrays (CFAs) for filtering light outside of a specific frequency range, one or more analog front ends for converting analog measurements to digital information, and / or other suitable components for imaging. The first lens 131 and the second lens 132 may have different fields of view for capturing different representations of a scene. For example, the first lens 131 may be an ultra-wide (UW) lens, and the second lens 132 may be a wide (W) lens. The multiple image sensors may include a combination of ultra-wide (high field of view (FOV)), wide, telephoto, and super-telephoto (low FOV) sensors. That is, each image sensor can be configured through hardware configuration and / or software settings to provide different but overlapping fields of view. In one configuration, the image sensors are configured with different lenses having different magnifications that result in different fields of view. The sensors can be configured such that the UW sensor has a larger FOV than the W sensor, which has a larger FOV than the T sensor, which has a larger FOV than the UT sensor. For example, a sensor configured for a wide FOV can capture a field of view ranging from 64 to 84 degrees, a sensor configured for an ultra-wide FOV can capture a field of view ranging from 100 to 140 degrees, a sensor configured for a telephoto FOV can capture a field of view ranging from 10 to 30 degrees, and a sensor configured for a super-telephoto FOV can capture a field of view ranging from 1 to 8 degrees.

[0035]

[0038] Image signal processor 112 processes image frames captured by image sensor 101 and image sensor 102. While FIG. 1 depicts device 100 as including two image sensors 101 and 102 coupled to image signal processor 112, any number of image sensors (e.g., 1, 2, 3, 4, 5, 6, etc.) may be coupled to image signal processor 112. In some aspects, a depth sensor, such as depth sensor 140, may be coupled to image signal processor 112, and output from the depth sensor may be processed in a similar manner as the output of image sensor 101 and image sensor 102. Furthermore, any number of additional image sensors or image signal processors may be present for device 100.

[0036]

[0039] In some embodiments, the image signal processor 112 may execute instructions from a memory, such as instructions 108 from memory 106, instructions stored in a separate memory coupled to or included within the image signal processor 112, or instructions provided by the processor 104. Additionally or alternatively, the image signal processor 112 may include specific hardware (such as one or more integrated circuits (ICs)) configured to perform one or more operations described in this disclosure. For example, the image signal processor 112 may include one or more image front ends (IFEs) 135, one or more image post-processing engines 136 (IPEs), and / or one or more auto exposure compensation (AEC) 134 engines. The AFs 133, AECs 134, AFEs 135, and APEs 136 may each include application-specific circuitry and may be embodied as software code executed by the ISP 112 and / or as a combination of hardware within the ISP 112 and software code executing on the ISP 112.

[0037]

[0040] In some implementations, memory 106 may include a non-transient or non-transitory computer-readable medium storing computer-executable instructions 108 for performing all or a portion of one or more operations described in this disclosure. In some implementations, instructions 108 include a camera application (or other suitable application) to be executed by device 100 to generate images or video. Instructions 108 may also include other applications or programs executed by device 100, such as an operating system and specific applications other than for image or video generation. Execution of the camera application, such as by processor 104, may cause device 100 to generate images using image sensors 101 and 102 and image signal processor 112. Memory 106 may also be accessed by image signal processor 112 to store processed frames or by processor 104 to retrieve processed frames. In some embodiments, device 100 does not include memory 106. For example, device 100 can be a circuit that includes image signal processor 112, and the memory can be external to device 100. Device 100 can be coupled to external memory and configured to access the memory to write output frames for display or long-term storage. In some embodiments, device 100 is a system on chip (SoC) that incorporates image signal processor 112, processor 104, sensor hub 150, memory 106, and input / output components 116 within a single package.

[0038]

[0041] In some embodiments, at least one of image signal processor 112 or processor 104 executes instructions to perform various operations described herein, including noise reduction operations. For example, execution of those instructions may instruct image signal processor 112 to begin or end capturing an image frame or a series of image frames, where the capturing includes noise reduction as described in embodiments herein. In some embodiments, processor 104 may include one or more general-purpose processor cores 104A capable of executing scripts or instructions of one or more software programs, such as instructions 108, stored in memory 106. For example, processor 104 may include one or more application processors configured to execute a camera application (or other suitable application for generating images or videos) stored in memory 106.

[0039]

[0042] When executing the camera application, processor 104 can be configured to instruct image signal processor 112 to perform one or more operations related to image sensor 101 or image sensor 102. For example, the camera application can receive a command to initiate a video preview display in which video including a series of image frames from one or more image sensors 101 or 102 is captured and processed. Image correction, such as by cascaded IPE, can be applied to one or more image frames in the sequence. Execution of instructions 108 other than the camera application by processor 104 can also cause device 100 to perform any number of functions or operations. In some embodiments, processor 104 can include ICs or other hardware (e.g., artificial intelligence (AI) engine 124) in addition to the ability to execute software to cause device 100 to perform any number of functions or operations, such as those described herein. In some other embodiments, device 100 does not include processor 104, such as when all of the described functionality is configured in image signal processor 112.

[0040]

[0043] In some embodiments, display 114 may include one or more suitable displays or screens that allow for user interaction and / or allow for presenting items to a user, such as previews of image frames being captured by image sensor 101 and image sensor 102. In some embodiments, display 114 is a touch-sensitive display. I / O components 116 may be or include any suitable mechanism, interface, or device for receiving input (e.g., commands) from a user and for providing output to the user via display 114. For example, I / O components 116 may include (without limitation) a graphical user interface (GUI), a keyboard, a mouse, a microphone, a speaker, a compressible bezel, one or more buttons (e.g., a power button), sliders, switches, etc.

[0041]

[0044] Although shown coupled to each other via processor 104, components (e.g., processor 104, memory 106, image signal processor 112, display 114, and I / O components 116) may be coupled to each other in various other configurations, such as via one or more local buses, not shown for simplicity. While image signal processor 112 is shown as separate from processor 104, image signal processor 112 may also be a core of processor 104, an application processor unit (APU), included within a system-on-chip (SoC) or otherwise included with processor 104. Although device 100 is referred to in examples herein for performing aspects of the present disclosure, some device components may not be shown in FIG. 1 to avoid obscuring aspects of the present disclosure. Furthermore, other components, multiple components, or combinations of components may be included in a device suitable for performing aspects of the present disclosure. Therefore, the present disclosure is not limited to any particular device or arrangement of components, including device 100.

[0042]

[0045] In some aspects, the ISP 112 can configure one or more of the IPEs 136 in a cascaded or serial configuration, such that the input of at least one of the IPEs becomes the output of another IPE. One example of a cascaded IPE configuration for an ISP is shown in FIG. 2. FIG. 2 is a block diagram illustrating a cascaded image post-processing engine (IPE) according to one or more aspects. The cascaded IPE 200 includes a first IPE 210 and a second IPE 230. The output of the first IPE 210 is input to the second IPE 230. If the cascaded series of IPEs is longer than two IPEs, the output of the second IPE 230 can be applied as an input to an additional IPE. The last IPE in the cascade of IPEs can output a corrected first image frame. The corrected first image frame can be used in a preview video display, for example, in a camera application, or can also be used to record a video sequence in memory.

[0043]

[0046] Each of the IPEs 210 and 230 can be a general-purpose IPE, i.e., each of the IPEs 210 and 230 can include circuitry for spatial noise reduction (NR) 212, 232, circuitry for temporal NR 214, 234, circuitry for color correction matrix (CCM) processing 216, 236, circuitry for tone mapping 218, 238, circuitry for gamma correction 220, 240, and circuitry for edge enhancement 222, 242. Although each of the IPEs 210 and 230 is a general-purpose processing unit, each of the IPEs 210 and 230 can be configured to perform operations specific to that IPE's position within a cascaded series of IPEs. For example, the IPE 210 can be configured to perform gamma correction 220 if the IPE 210 is the first stage of a cascaded series of IPEs, and the IPE 230 can be configured to disable gamma correction 240 if the IPE 230 is the second or subsequent stage of a cascaded series of IPEs. As another example, only one IPE of a cascaded series of IPEs can be configured with color correction matrix (CCM) processing enabled. As a further example, each of the IPEs 210 and 230 can include circuitry for tone mapping 218, 238, but can be configured with different mappings. For example, the circuitry in the IPE 210 for tone mapping 218 can apply a first tone mapping to change the tone of an entire image frame, and the circuitry in the IPE 230 for tone mapping 238 can apply a second tone mapping for contrast enhancement and / or brightness enhancement.

[0044]

[0047] Cascaded IPEs can be used to perform noise reduction and enhance brightness. Cascading two or more IPEs to enhance brightness may implement multiple noise reductions without the adverse effects of noise added by the brightness enhancement. The cascaded noise reduction of cascaded IPEs can produce corrected image frames with less noise, sharper colors, brighter frames, and / or enhanced contrast edges. Brightness enhancement is useful in low-light photography to enhance image detail without significantly increasing noise common in low-light photography or while reducing noise common in low-light photography. Processing image frames through cascaded IPEs can advantageously be applied to image frames captured from small optical format (e.g., small pixel) sensors, since small-format sensors may have reduced low-light photography due to capturing less light than larger format sensors for a given exposure time.

[0045]

[0048] Example results from a test scene captured by an image sensor and processed with one IPE and two cascaded IPEs are shown in Table 1, which demonstrates improved texture, reduced noise, and increased brightness values ​​when processing an image frame using a cascade of two IPEs, all of which are improvements over the values ​​obtained when processing an image frame using a single IPE.

[0046] [Table 1]

[0047]

[0049] A method for processing an image frame using two or more noise reduction and tone mapping operations to improve the appearance of the image frame is illustrated in the flowchart of FIG. 3. FIG. 3 is a flowchart illustrating a method for processing an image frame using multiple noise reduction operations according to one or more aspects. In some embodiments, the method of FIG. 3 may be implemented in multiple hardware IPE blocks, such as those shown in FIG. 2. However, the method of FIG. 3 may also be implemented using a single hardware IPE block, other application-specific circuit configurations, and / or on a general-purpose processor. Method 300 begins with receiving a first image frame at block 302. Prior to receiving the first image frame at block 302, the first image frame may be captured by a first image sensor and processed via an image front end (IFE). In some embodiments, the first image frame may be a composite output of multiple image frames captured from one or more image sensors, such as when the first image frame is a high dynamic range (HDR) image frame generated from multiple exposures of one or more image sensors.

[0048]

[0050] A first sequence of image processing operations includes blocks 304, 306, 308, and 310. In block 304, first noise reduction is performed on the first image frame. The first noise reduction may include spatial and / or temporal noise reduction. In block 306, a color correction matrix (CCM) is applied, such as to produce more vivid colors in the image frame. In block 308, a first tone mapping is applied. Tone mapping can be used to map one set of colors to another set of colors to create a particular artistic effect in the image. In some embodiments, the first tone mapping in block 308 can be applied to the first image frame to approximate the appearance of a high dynamic range image in a medium with a more limited dynamic range. In block 310, gamma correction is applied to enhance brightness in the first image frame. Each of the operations in blocks 304, 306, 308, and 310 can access and modify values ​​in memory corresponding to the first image frame. Thus, the input of one of processing blocks 304, 306, 308, and 310 is the output of another of processing blocks 304, 306, 308, and 310. The processing performed before the second noise reduction in block 312 may also be performed in a different order than shown in Figure 3, such as by applying the tone mapping in block 308 after the gamma correction in block 310. In some embodiments, the first sequence of operations in blocks 304, 306, 308, and 310 may be performed by a first hardware circuit, such as a first IPE.

[0049]

[0051] A second sequence of image processing operations includes blocks 312, 314, and 316. In block 312, a second noise reduction is performed on the first image frame as modified by the first sequence of processing operations of blocks 304, 306, 308, and 310. In block 314, a second tone mapping is applied. The second tone mapping may be different from the tone mapping of block 308. For example, different maps may be used to modify the image frames input to blocks 308 and 314. The second tone mapping may be configured to provide contrast enhancement and brightness enhancement, rather than a general artistic color mapping as in the first tone mapping of block 308. In block 316, the first image frame as modified by the first sequence of image processing operations of blocks 304, 306, 308, and 310, and further modified by the second sequence of image processing operations of blocks 312, 314, and 316, is output as a corrected first image frame. The corrected first image frame may be used, for example, along with other image frames that may or may not have been similarly processed, to generate a video sequence and may be displayed to a user of the image capture device as a preview stream in a camera application.

[0050]

[0052] One example of the processing flow for image frames as part of a video sequence in an image capture device is shown in FIG. 4. FIG. 4 is a block diagram illustrating the processing flow for image frames through cascaded image post-processing engines (IPEs) in accordance with one or more aspects. An image sensor 402 generates a series of image frames, including a first image frame representing a scene 404. An image signal processor 410 can receive the series of image frames and perform real-time processing on the image frames, thereby generating and displaying an output video sequence to a user to monitor the scene 404 in real time, such that changes in the scene can be perceived by the user in a time approximating the time at which the changes occur (e.g., within less than 500 milliseconds, less than 400 milliseconds, less than 300 milliseconds, less than 200 milliseconds, or less than 100 milliseconds). The ISP 410 can have multiple IPEs, such as IPE 412A and IPE 412B, to flexibly process the image frames received by the ISP 410. For example, the ISP 410 can use different IPEs in parallel to process image frames received in parallel from different image sensors. In another embodiment, the ISP 410 can use different IPEs in series to process image frames received from a single image sensor.

[0051]

[0053] The ISP 410 can determine the camera configuration, such as by receiving the configuration from a camera application running on the image capture device, and appropriately allocate available IPEs to specific processes within the ISP 410. In one embodiment, the camera application can specify whether to apply a cascaded IPE configuration based on a user setting for activating a “low light” or “night vision” mode or by applying one or more rules to the image frame to determine whether to activate the cascaded IPE. If a low light condition or other condition exists to trigger the cascaded IPE, the first image frame received from the sensor can be processed to generate an intermediate first image frame in response to determining the low light condition or other condition for activating the cascaded IPE. Alternatively, or in addition, the ISP can determine when to activate a cascaded IPE configuration based on the same or different conditions. The conditions for applying the cascaded IPE configuration or determining the ISP can be a combination of one or more factors, including exposure gain, exposure time, lux index, and video frames per second (FPS). For example, cascaded IPE can be configured when the exposure gain, exposure time, and lux index each exceed a certain threshold, or when their combined values ​​exceed a certain threshold. The lower the video FPS, the longer the exposure time provided for the image frames of the video sequence. Therefore, the video FPS can be used to adjust the threshold used to trigger the cascaded IPE or can be factored into the value compared to the threshold.The determination of the IPE configuration (e.g., single IPE or cascaded IPEs) can be performed before receiving the first image frame for processing (e.g., as a configuration in a camera application and / or based on previous image frames processed by an ISP), after receiving the first image frame (e.g., by determining statistics from the first image frame), and / or on an intermediate first image frame (e.g., by determining statistics from the first image frame after processing through the first IPE). If a single IPE configuration is determined, other noise reduction processes can be applied, such as multi-frame noise reduction by fusing the output of the single IPE with another image frame.

[0052]

[0054] In some embodiments, the ISP 410 can configure one or more IPEs to perform cascaded operations similar to those described in connection with Figures 2 and 3. For example, the ISP 410 can cascade two separate IPEs, 412A and 412B, to perform operations associated with a first noise reduction operation and a second noise reduction operation, respectively. For example, the IPE 412A can be configured similar to the IPE 210 of Figure 2, and the IPE 412B can be configured similar to the IPE 230 of Figure 2. The IPE 412A can perform operations associated with blocks 304, 306, 308, 310, and 312 of Figure 3, and the IPE 412B can perform operations associated with blocks 310, 312, and 314. IPE 412A and IPE 412B can be serially coupled such that the output of IPE 412A is input to IPE 412B, and the output of IPE 412B is an output video sequence including at least the corrected first image frame. Processing in IPE 412B can be determined by 3A metadata (including one or more of exposure gain, exposure time, lux index, white balance WB gain, and corrected color temperature CCT). In some embodiments, ISP 410 can cascade IPEs using a single IPE by using a loopback from the output of the IPE back to the input of the IPE and reconfiguring the IPE to perform a second set of noise reduction operations.

[0053]

[0055] In one or more aspects, techniques for supporting image enhancement using cascaded IPEs may include additional aspects, such as any single aspect or any combination of aspects, described below or in connection with one or more other processes or devices described elsewhere herein. In some implementations, the apparatus includes a wireless device such as a UE. In some implementations, the apparatus may include at least one processor and a memory coupled to the processor. The processor may be configured to perform operations described herein. In some other implementations, the apparatus may include a non-transitory computer-readable medium having program code recorded thereon, the program code being executable by the processor to cause the apparatus to perform operations described herein in connection with the apparatus. In some implementations, the apparatus may include one or more means configured to perform the operations described herein. In some implementations, a method of wireless communication may include one or more operations described herein for processing image frames using cascaded IPEs.

[0054]

[0056] Those skilled in the art will appreciate that information and signals may be represented using any of a wide variety of technologies and techniques. For example, the data, instructions, commands, information, signals, bits, symbols, and chips that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

[0055]

[0057] The components, functional blocks, and modules described herein with respect to Figures 1-4 include, among numerous examples, processors, electronic devices, hardware devices, electronic components, logic circuits, memories, software code, firmware code, or any combination thereof. Software should be construed broadly to mean, among numerous examples, instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, and / or functions, whether referred to as software, firmware, middleware, microcode, hardware description language, etc. Furthermore, features discussed herein can be implemented via dedicated processor circuitry, via executable instructions, or combinations thereof.

[0056]

[0058] Those skilled in the art will further appreciate that the various illustrative logic blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein can be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability between hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the particular application and design constraints imposed on the overall system. Those skilled in the art may implement the described functionality in various ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure. Those skilled in the art will also readily recognize that the ordering or combination of components, methods, or interactions described herein are merely examples, and that the components, methods, or interactions of various aspects of the present disclosure can be combined or performed in ways other than those shown and described herein.

[0057]

[0059] The various example logic, logic blocks, modules, circuits, and algorithmic processes described in connection with the implementations disclosed herein may be implemented as electronic hardware, computer software, or a combination of both. Interchangeability between hardware and software has been generally described in terms of functionality and is illustrated in the various example components, blocks, modules, circuits, and processes described above. Whether such functionality is implemented in hardware or software depends upon the particular application and design constraints imposed on the overall system.

[0058]

[0060] Hardware and data processing devices used to implement the various example logic, logic blocks, modules, and circuits described in connection with aspects disclosed herein may be implemented or performed using general-purpose single-chip or multi-chip processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic, discrete hardware components, or any combination thereof, designed to perform the functions described herein. A general-purpose processor may be a microprocessor, or any conventional processor, controller, microcontroller, or state machine. In some implementations, a processor may be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. In some implementations, particular processes and methods may be performed by circuitry that is specialized for a given function.

[0059]

[0061] In one or more aspects, the functions described may be implemented in hardware, digital electronic circuitry, computer software, firmware, or any combination thereof, including the structures disclosed herein and their structural equivalents. Implementations of the subject matter described herein may also be implemented as one or more computer programs, i.e., as one or more modules of computer program instructions encoded on a computer storage medium for execution by, or to control the operation of, a data processing apparatus.

[0060]

[0062] If implemented in software, the functions can be stored on or transmitted over as one or more instructions or code on a computer-readable medium. The processes of a method or algorithm disclosed herein can be implemented in a processor-executable software module, which can reside on a computer-readable medium. Computer-readable media includes both computer storage media and communication media, including any medium capable of enabling transfer of a computer program from one place to another. A storage medium can be any available medium that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can include random-access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection can be properly termed a computer-readable medium. Disk and disc, as used herein, include compact discs (CDs), laser discs, optical discs, digital versatile discs (DVDs), floppy disks, and Blu-ray discs, where disks typically reproduce data magnetically, while discs reproduce data optically using a laser. Combinations of the above should also be included within the scope of computer-readable media.Furthermore, the operations of a method or algorithm may reside as code and instructions, one or any combination or set, on a machine-readable medium and a computer-readable medium, which may be embodied in a computer program product.

[0061]

[0063] Various modifications to the implementations described in this disclosure will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to several other implementations without departing from the spirit or scope of the present disclosure. Thus, the claims are not intended to be limited to the implementations shown herein, but are to be accorded the widest scope consistent with the present disclosure and the principles and novel features disclosed herein.

[0062]

[0064] Furthermore, those skilled in the art will readily appreciate that the terms "upper" and "lower" may be used to facilitate description of the figures and indicate relative positions corresponding to the orientation of the figures on a properly oriented page, but may not reflect the proper orientation of any device in which they may be implemented.

[0063]

[0065] Certain features that are described herein in the context of separate implementations can also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations separately or in any suitable subcombination. Furthermore, while features may be described above as working in a particular combination, and may even be originally claimed as such, one or more features from a claimed combination may in some cases be deleted from the combination, and the claimed combination may be directed to a subcombination or a variation of the subcombination.

[0064]

[0066] Similarly, while acts are shown in the figures in a particular order, this should not be understood as requiring that such acts be performed in the particular order shown, or sequential order, or that all of the acts shown be performed, to achieve desirable results. Furthermore, the figures may generally depict one or more exemplary processes in the form of flow diagrams. However, other acts not shown may be incorporated into the generally depicted exemplary process. For example, one or more additional acts may be performed before, after, simultaneously with, or between any of the depicted acts. In certain situations, multitasking and parallel processing may be advantageous. Furthermore, the separation of various system components in the above-described implementations should not be understood as requiring such separation in all implementations, and it should be understood that the described program components and systems may generally be integrated together in a single software product or packaged in multiple software products. Furthermore, several other implementations are within the scope of the following claims. In some cases, the actions recited in the claims may be performed in a different order and still achieve desirable results.

[0065]

[0067] As used herein, including the claims, the term "or," when used in a list of two or more items, means that any one of the listed items may be employed alone, or any combination of two or more of the listed items may be employed. For example, if a composition is described as containing components A, B, or C, the composition may contain only A, only B, only C, a combination of A and B, a combination of A and C, a combination of B and C, or a combination of A, B, and C. Also, as used herein, including the claims, "or," as used in a list of items ending with "at least one of," indicates a disjunctive list, such that, for example, a list of "at least one of A, B, or C" means any of A, or B, or C, or AB, or AC, or BC, or ABC (i.e., A and B and C), or any of them in any combination thereof. The term "substantially," as understood by one of ordinary skill in the art, is defined as to the majority of, but not necessarily to the entirety of, what is specified (and is inclusive of what is specified, e.g., substantially 90 degrees includes 90 degrees, and substantially parallel includes parallel). In any of the disclosed implementations, the term "substantially" can be replaced with "within a percentage of" what is specified, where percentage includes 0.1, 1, 5, or 10 percent.

[0066]

[0068] The above description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the disclosure is not intended to be limited to the embodiments and designs described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein. The inventions described in the claims of the present application as originally filed are set forth below. [C1] Receiving a first image frame; processing the first image frame through a first pass through an image correction algorithm having a first configuration to generate an intermediate first image frame, wherein the first configuration results in the processing including a first set of operations associated with a first noise reduction operation; processing the intermediate first image frame through a second pass through the image correction algorithm having a second configuration to generate a corrected first image frame, wherein the second configuration results in the processing including a second set of operations associated with a second noise reduction operation; A method comprising: [C2] The method of C1, further comprising forming a video sequence including the corrected first image frame and at least one corrected second image frame. [C3] storing the video sequence in a memory; transmitting said video sequence over a wireless network; or displaying the video sequence on a display; The method of C2, further comprising at least one of: [C4] processing the first image frame through a first pass in an image correction algorithm comprises processing the first image frame through a first image post-processing engine (IPE); processing the intermediate first image frame through a second pass through the image correction algorithm comprises processing the first image frame through a second image post-processing engine (IPE). The method of any one of C1, 2, or 3. [C5] The method according to any one of C1 to C4, wherein the first IPE is the same as the second IPE. [C6] The first configuration for a first image correction algorithm comprises applying a first tone mapping; the second configuration for a second image correction algorithm comprises applying a different second tone mapping for contrast enhancement and brightness enhancement. The method according to any one of C1 to C5. [C7] The first configuration for the first image correction algorithm comprises applying gamma correction; the second configuration for the image correction algorithm does not comprise applying gamma correction; The method according to any one of C1 to C6. [C8] wherein only one of the first image correction algorithm and the second image correction algorithm comprises applying a color correction matrix. The method according to any one of C1 to C7. [C9] determining that a low light condition exists in the first image frame; processing the first image frame and processing the intermediate first image frame in response to the determination of the low light condition; The method according to any one of C1 to C8, further comprising: [C10] determining that a low light condition is not present in the first image frame; receiving a second image frame in response to determining that the low light condition does not exist; and processing the intermediate image frame and the second image frame to determine a corrected first image frame having reduced noise using a multi-frame noise reduction (MFNR) algorithm; The method of C9, further comprising: [C11] Receiving a first image frame; applying a first noise reduction to the first image frame; applying a first tone mapping to the first image frame after applying the first noise reduction; applying gamma correction to the first image frame after applying the first tone mapping; applying a second noise reduction to the first image frame after applying the gamma correction; applying a second tone mapping to the first image frame after applying the second noise reduction; applying a color correction matrix to the first image frame after applying the first noise reduction; outputting a corrected first image frame after applying the first noise reduction, applying the first tone mapping, applying the gamma correction, applying the second noise reduction, applying the second tone mapping, and applying the color correction matrix; A method comprising: [C12] a first image post-processing engine (IPE) performs the steps of applying the first noise reduction, applying the first tone mapping, and applying the gamma correction; a second image post-processing engine (IPE) performing the second applying noise reduction and the second applying tone mapping; The method described in C11. [C13] determining that a low light condition exists in the first image frame; in response to determining that the low light condition exists, performing the steps of applying the first noise reduction, applying the first tone mapping, applying the gamma correction, applying the second noise reduction, and applying the second tone mapping; 13. The method of any one of C11 or 12, further comprising: [C14] forming a video sequence comprising the corrected first image frame and at least one corrected second image frame; storing the video sequence in a memory; transmitting said video sequence over a wireless network; or displaying the video sequence on a display; At least one of the following: The method according to any one of C11 to C13, further comprising: [C15] An apparatus comprising an image signal processor, the apparatus comprising a plurality of image post-processing engines (IPEs), the IPE including at least a first IPE and a second IPE, the image signal processor receiving a first image frame; processing the first image frame using the first IPE to generate an intermediate first image frame; The apparatus is configured to process the intermediate first image frame using a second IPE to generate a corrected first image frame. [C16] The image signal processor applying a first noise reduction; applying a first tone mapping; applying gamma correction; and wherein the image signal processor is configured to configure the first IPE to perform steps comprising: applying a second noise reduction; applying a second tone mapping; and configuring the second IPE to perform steps comprising: The apparatus described in C15. [C17] The apparatus of any one of C15 or 16, wherein the image signal processor is configured to configure one of the first IPE or the second IPE to apply a color correction matrix. [C18] The apparatus of any one of C15 to C17, wherein the image signal processor is configured to configure the second IPE to not apply gamma correction. [C19] The apparatus of any one of C15 to C18, wherein the image signal processor is configured to allocate the plurality of IPEs to process image frames from one or more image sensors. [C20] Memory and An apparatus comprising: at least one processor configured to perform the operations of the method according to any one of C1 to C14. [C21] The apparatus of C20, wherein the at least one processor comprises an image signal processor. [C22] The apparatus of any one of C20 or 21, wherein the at least one processor comprises a graphics processing unit (GPU). [C23] The apparatus of any one of C20 to C22, wherein the at least one processor comprises a central processing unit (CPU). [C24] The apparatus according to any one of C15 to C23, wherein the apparatus comprises an image capture device.

Claims

1. receiving a first image frame; processing the first image frame through a first pass in a first image correction algorithm having a first configuration to generate an intermediate first image frame, wherein the first configuration results in the processing including a first set of operations associated with a first noise reduction operation, and wherein processing the first image frame through the first pass in the first image correction algorithm comprises processing the first image frame through a first image post-processing engine (IPE) of a plurality of cascaded image post-processing engines (IPEs); processing the intermediate first image frame through a second pass in a second image correction algorithm having a second configuration to generate a corrected first image frame, wherein the second configuration results in the processing including a second set of operations associated with a second noise reduction operation, and wherein processing the intermediate first image frame through the second pass in the second image correction algorithm comprises processing the intermediate first image frame through a second image post-processing engine (IPE) of the cascaded plurality of IPEs; A method comprising:

2. The method of claim 1 , further comprising forming a video sequence including the corrected first image frame and at least one corrected second image frame.

3. storing the video sequence in a memory; transmitting said video sequence over a wireless network; or displaying the video sequence on a display; The method of claim 2 , further comprising at least one of:

4. The method of claim 1 , wherein the first IPE is the same as the second IPE.

5. the first configuration for the first image enhancement algorithm comprises applying a first tone mapping; the second configuration for the second image correction algorithm comprises applying a different second tone mapping for contrast enhancement and brightness enhancement. The method of claim 1.

6. the first configuration for the first image correction algorithm comprises applying gamma correction; the second configuration for the second image correction algorithm does not comprise applying gamma correction; The method of claim 1.

7. only one of the first image correction algorithm and the second image correction algorithm comprises applying a color correction matrix. The method of claim 1.

8. determining that a low light condition exists within the first image frame; processing the first image frame and processing the intermediate first image frame in response to the determination of the low light condition; The method of claim 1 further comprising:

9. determining that a low light condition is not present in the first image frame; receiving a second image frame in response to determining that the low light condition does not exist; and processing the intermediate first image frame and the second image frame to determine a corrected first image frame having reduced noise using a multi-frame noise reduction (MFNR) algorithm; The method of claim 8 further comprising:

10. Processing the first image frame includes: applying a first noise reduction to the first image frame; applying a first tone mapping to the first image frame after applying the first noise reduction; applying gamma correction to the first image frame after applying the first tone mapping; Equipped with Processing the intermediate first image frame includes: applying a second noise reduction to the first image frame after applying the gamma correction; applying a second tone mapping to the first image frame after applying the second noise reduction; applying a color correction matrix to the first image frame after applying the first noise reduction; Equipped with outputting the corrected first image frame after applying the first noise reduction, applying the first tone mapping, applying the gamma correction, applying the second noise reduction, applying the second tone mapping, and applying the color correction matrix; The method of claim 1 , comprising:

11. the first image post-processing engine (IPE) performs the steps of applying the first noise reduction, applying the first tone mapping, and applying the gamma correction; the second image post-processing engine (IPE) performs the steps of applying the second noise reduction and applying the second tone mapping; The method of claim 10.

12. determining that a low light condition exists within the first image frame; in response to determining that the low light condition exists, performing the steps of applying the first noise reduction, applying the first tone mapping, applying the gamma correction, applying the second noise reduction, and applying the second tone mapping; The method of claim 10 further comprising:

13. forming a video sequence comprising the corrected first image frame and at least one corrected second image frame; storing the video sequence in a memory; transmitting said video sequence over a wireless network; or displaying the video sequence on a display; At least one of the following: The method of claim 10 further comprising:

14. 1. An apparatus comprising an image signal processor comprising a plurality of cascaded image post-processing engines (IPEs), the IPEs including at least a first IPE and a second IPE, the image signal processor receiving a first image frame; processing the first image frame using the first IPE to generate an intermediate first image frame; configured to process the intermediate first image frame using a second IPE to generate a corrected first image frame; the first IPE and the second IPE are coupled in series such that the output of the first IPE is the input of the second IPE and the output of the second IPE is the corrected first image frame.

15. the image signal processor applying a first noise reduction; applying a first tone mapping; applying gamma correction; and wherein the image signal processor is configured to configure the first IPE to perform steps comprising: applying a second noise reduction; applying a second tone mapping; and configuring the second IPE to perform steps comprising:

15. The apparatus of claim 14.

16. 15. The apparatus of claim 14, wherein the image signal processor is configured to configure one of the first IPE or the second IPE to apply a color correction matrix.

17. 15. The apparatus of claim 14, wherein the image signal processor is configured to configure the second IPE to not apply gamma correction.

18. The apparatus of claim 14 , wherein the image signal processor is configured to allocate the plurality of IPEs to process image frames from one or more image sensors.

19. Memory and At least one processor configured to perform the operations of the method according to any one of claims 1 to 13.

20. 20. The apparatus of claim 19, wherein the at least one processor comprises an image signal processor.

21. 20. The apparatus of claim 19, wherein the at least one processor comprises a graphics processing unit (GPU).

22. 20. The apparatus of claim 19, wherein the at least one processor comprises a central processing unit (CPU).

23. The apparatus of claim 14 , wherein the apparatus comprises an image capture device.

Images