281 results about "Image quality degradation" patented technology

The invention discloses a valve support quality detection method based on image recognition, and particularly relates to the technical field of valve support quality detection.The method comprises the steps that real-time temperature data and image data in the valve support quality detection process are acquired; outputting a temperature-image relation model through joint calibration of a temperature sensor and an image sensor; compensating the image data of the valve bracket based on the real-time temperature data and the temperature-image relation model; building an initial defect identification model, adjusting model parameters based on the real-time temperature data and the preliminarily compensated image, using a time sequence causal relationship model to predict image quality degradation, adjusting the model parameters in advance, and outputting a trained defect identification model; controlling a receptive field and a feature fusion coefficient of the defect identification model; the feature fusion coefficient is used for adjusting the feature fusion weight of each scale; and the training priority is managed by using clustering analysis, and the detection precision of the temperature anomaly region is optimized.

The invention discloses a nighttime image enhancement method based on multidirectional information extraction and color loss optimization, which comprises the following steps: firstly, collecting nighttime and normal light road scene images, constructing a nighttime road image enhancement model based on deep learning, and adopting an image enhancement framework based on GAN and a superficial layer semantic enhanced U-Net network as a generator; the five-layer convolutional network is used as a discriminator, then horizontal-vertical bidirectional differential convolution is used to extract multi-directional information of the image, a local illumination attention module is used to balance dark area brightness and bright area overexposure, and finally an adaptive color loss function is used to recover original colors of the image. The method can effectively solve the problems of image quality reduction, detail loss, color distortion and the like under the low-illumination condition, and is particularly suitable for night scene visual perception improvement in the field of vehicle-assisted automatic driving.

The invention relates to the technical field of embankment inspection, and provides an embankment inspection robot environment detection method and system, which can determine a motion blur direction, extract linear features of an image and determine a linear feature direction by acquiring an embankment image and performing motion blur judgment when the image has motion blur. And on the basis, according to the geometrical relationship between the motion blur direction and the linear feature direction, whether the linear feature is the embankment crack or not is judged. By using the motion blur direction as a judgment basis, a pseudo crack and a real crack caused by motion blur can be effectively distinguished, and early-stage potential safety hazard detection omission caused by image quality reduction is avoided, so that the accuracy and the reliability of embankment crack detection are remarkably improved, and the continuity and the effectiveness of an embankment inspection task are guaranteed.

The invention belongs to the technical field of photoelectric detection, and particularly relates to a super-large field-of-view circumferential scanning imaging system and a control method thereof.The system comprises a rotary table, an orientation fast reflecting mirror, a pitching fast reflecting mirror, an optical mirror set, an imaging assembly, a master control unit and an image processing unit; meanwhile, the invention further provides a super-large field-of-view circumferential scanning imaging control method, in the process that the rotary table rotates to drive the imaging assembly to carry out rapid imaging, image motion of an image in the process that the rotary table rotates at a constant speed is eliminated through the orientation fast reflecting mirror, and the problem that the image quality of an imaging assembly detector is reduced in the dynamic process is solved; through point-to-point pointing movement of the pitching fast reflecting mirror, an ultra-large field-of-view imaging function in the pitching direction is realized. By reasonably controlling the rotary table and scheduling the orientation fast reflecting mirror and the pitching fast reflecting mirror in the light path, accurate pointing of light beams and stable output of images are achieved, and the requirements for the imaging quality, the coverage range and the real-time performance are met.

The invention discloses an HDR dynamic tone mapping method and system. The HDR dynamic tone mapping method comprises the following steps: S1, acquiring an ambient light parameter, a user interaction parameter and a display equipment state parameter which are acquired in real time; s2, performing dynamic parameter fusion on the ambient light parameters, the user interaction parameters, the display equipment state parameters and video content metadata to generate dynamic metadata; s3, generating a self-adaptive tone mapping curve based on the dynamic metadata, wherein the self-adaptive tone mapping curve adjusts a brightness mapping relation through an equipment aging compensation parameter; and S4, measuring the error between the actual display image quality and the theoretical value, and correcting the compensation parameter in the dynamic parameter fusion according to the error value. According to the method, various parameters are collected in real time, the adaptive tone mapping curve is generated through dynamic fusion, and errors are corrected in combination with closed-loop feedback, so that the problem of image quality degradation caused by environment change, equipment aging and user interaction difference in the traditional HDR technology is solved, and high-precision and adaptive dynamic display optimization is realized.

The invention relates to the technical field of target tracking, provides a low-light environment target tracking method based on image channel enhancement and dynamic attention feature matching, and solves the problems of difficult feature extraction, mismatching, insufficient real-time performance and the like caused by image quality degradation in a low-light and resource-limited scene in a traditional method. The method comprises the following steps of: distributing enhanced brightness and chrominance channels by adopting a YUV spatial separation mechanism, realizing color restoration and noise suppression, and forming high-quality tracking input through cross-channel re-calibration; search calculation is accelerated based on a dynamic Transform architecture, and the feature matching capability is enhanced through cross attention fusion and interaction of global features. According to the method, an end-to-end collaborative architecture is adopted, image enhancement and target tracking are unified, and the method has the advantages of stable feature alignment capability and lightweight calculation design, and is suitable for application scenes such as unmanned aerial vehicle night cruise, security monitoring and edge calculation terminals with high requirements for real-time performance and robustness.

The invention discloses an underwater image degradation diffusion self-supervised enhancement model and a building and training method, and relates to the technical field of underwater image enhancement. The invention provides an underwater image degradation diffusion self-supervised enhancement model and a building and training method for the problem of target detection performance reduction caused by underwater image quality degradation, the model built by the method is combined with the differential thought of a Koschmieder illumination scattering degradation model and a diffusion model, the degradation process of a real underwater environment is simulated, and the target detection performance is improved. Self-supervised training data is generated, dependence of a traditional method on manual annotation data is avoided, image features are extracted through a ResNet50 backbone network, global background light and transmission rate are predicted in parallel, a clear image is reversely recovered by using a physical formula, transmission rate consistency loss, background light consistency loss and reconstruction loss are also proposed, an unsupervised optimization target is constructed, and the self-supervised training data is obtained. And the accuracy and stability of model training are ensured.

The invention provides an electricity meter reading method and device based on image recognition, equipment and a medium, and relates to the technical field of electricity charge settlement, and the method comprises the steps: obtaining the image information and environment information of an electricity meter; obtaining an image recognition reliability score; obtaining a fused image data set; carrying out image structure identification processing based on the fused image data set, and constructing an ammeter reading area model; performing integration and association reasoning on the fused image data set, the identification reliability score and the ammeter reading area model based on a preset graph neural network identification model to generate a comprehensive identification view; and obtaining an electricity meter reading identification result. According to the invention, through introduction of fusion processing of image information and environment information, a graph neural network identification model and a time sequence verification mechanism, multi-dimensional intelligent identification of ammeter reading is realized. Therefore, the electric meter identification accuracy and robustness in a complex scene are effectively improved, and the misreading rate caused by shooting environment interference, electric meter shielding or image quality reduction is remarkably reduced.

The invention relates to a coal mine scraper conveyor self-adaptive deviation correction method and system based on visual recognition, and relates to the technical field of coal mine conveying deviation correction, and the method comprises the steps that original time sequence image streams of a scraper chain and a ledge area of a target scraper conveyor are continuously obtained through an anti-explosion visual collection device; constructing an image cleanliness evaluation model, carrying out frame-by-frame analysis on the original time sequence image flow, and calculating and outputting a corresponding image cleanliness coefficient; dynamically configuring a grading decision-making mechanism by combining real-time working condition parameters of the target scraper conveyor based on the image cleanliness coefficient; and based on the corrected decision threshold and the image cleanliness coefficient, activating a corresponding decision mode, generating a deviation correction control quantity adaptive to the current working condition, and driving to execute adaptive deviation correction. The method solves the problems that a traditional correction method is difficult to deal with a coal mine high-dust environment, and false alarm, missing alarm and control disorder are likely to occur due to image quality degradation.

The invention discloses an image processing system based on the Internet of Things, which relates to the field of image processing technology and comprises a multispectral sensor integration module, an image feature extraction module, an edge computing module, a cloud computing guidance module, a dynamic task scheduling module and an edge-cloud feedback closed-loop module; the multispectral sensor integration module collects image data through the collaborative work of visible light and infrared light sensors; the image feature extraction module is used to extract valuable features from the image data; the edge computing module is used to realize adaptive compression; the cloud computing guidance module classifies the noise type in the image through a noise classification network; the dynamic task scheduling module comprises a high-performance mode, a basic mode and an emergency power-saving mode; the edge-cloud feedback closed-loop module regularly uploads the image quality index after noise reduction to the cloud; the invention effectively solves the problems of image noise and image quality degradation in a low-light environment while maintaining high computing efficiency and real-time performance.

The invention discloses a bridge side falling behavior sensing method and system suitable for low-quality visual conditions, and belongs to the technical field of behavior sensing. The method comprises the following steps: judging whether weak light and / or blur exists in a bridge side scene image according to a calculated TBV index of the bridge side scene image; the bridge side scene image with the weak light is input into the D2A-DCE model, the bridge side scene image with the blurring is input into the improved NAFNet model, the bridge side scene image with the weak light and the blurring is sequentially input into the D2A-DCE model and the improved NAFNet model, and a bridge side scene enhanced image is output; inputting the bridge side scene enhanced image into the improved CMFF model, and outputting a fusion feature map; and inputting the fusion feature map into a pre-constructed Bridge-SIDE Net model, and outputting a bridge side falling behavior sensing result. According to the invention, the problems of poor bridge side behavior identification accuracy, false report and missing report in an image quality degradation environment can be solved.

The invention discloses a picture defogging method based on fog concentration information guidance, and aims to solve the problem of image quality degradation in a natural dense fog environment, restore details and textures of a picture and improve the image quality. The method comprises a shallow feature extraction network and a deep defogging network. The shallow feature extraction network is composed of a common convolutional network and a multi-scale feature alignment module, and performs preliminary feature extraction and processing on an input image. The deep defogging network is composed of a fog concentration information estimation module and a basic encoder-decoder network, the fog concentration information estimation module generates a fog concentration mask graph by adopting a multi-head self-attention mechanism, and an encoder enhances feature expressive force through a plurality of dynamic convolutional layers and a channel attention mechanism; and the decoder gradually restores the image through the dynamic convolution layer and the conventional convolution layer to ensure the quality of the output image. Experimental results show that the method disclosed by the invention can effectively remove the haze area in a real foggy scene, the defogging effect is remarkably improved, and the definition and details of the image are recovered.

The invention discloses a hierarchical image rain removal method based on enhanced rain stripe perception. According to the method, for the problem of image quality degradation in a rainy day environment, an enhanced rain stripe perception feature enhancement module E-RAFEM is designed, two core components of a learnable direction filter and rain stripe texture modeling are integrated, and the directivity and linear texture features of rain stripes are accurately modeled. An encoder-decoder backbone network based on Transform is adopted, and E-RAFEM modules are embedded in the first three encoding levels, so that a hierarchical rain stripe processing mechanism is formed. A progressive multi-scale fusion mechanism is introduced, multi-scale features are captured through convolution kernels with different expansion rates, and gradual integration is carried out in a progressive mode to avoid information loss. According to the enhanced rain stripe sensing network ERA-Net provided by the invention, high-quality recovery of images under various complex rainy day conditions is realized through accurate rain stripe feature modeling and hierarchical processing strategies.

A system and method for real time discrete cosine transform image and video processing with convolutional neural network architecture. The system and method transforms degraded inputs into subband images, which are analyzed by a machine learning classification network to identify specific types of blur and compression artifacts. The classification network dynamically adjusts the parameters of separate DC and AC deblurring networks based on its analysis. This adaptive approach optimizes processing for various degradation types, improving the quality of the reconstructed output. The system and method's real-time capability and enhanced adaptability make it suitable for a wide range of imaging and video applications, offering superior performance over traditional methods.

The invention relates to the technical field of goods identification of a laneway stacker, in particular to a goods identification method and system of the laneway stacker, and the method comprises the following steps: collecting a goods image; performing quality evaluation on the cargo image, and judging the degradation type of the cargo image; based on the degradation type, performing adaptive image enhancement processing on the cargo image to obtain an enhanced image; generating a feature descriptor having resistance to the degradation influence of the cargo image; inputting the enhanced image and the feature descriptor into a deep learning model for cargo identification to obtain an identification result and confidence; and performing identification process control according to the confidence coefficient. According to the method, the recognition accuracy and stability of the deep learning model can be improved, so that the problems of recognition failure and efficiency reduction caused by image quality reduction are effectively solved.

Due to the fact that the space and the loading capacity of a quadrotor unmanned aerial vehicle platform are limited and a radar and the unmanned aerial vehicle are installed in a hard connection mode, attitude changes and motion errors of the unmanned aerial vehicle platform can be directly transmitted to the radar, radar beams have large deviation and shaking in the imaging working process, motion error compensation is difficult, and the imaging efficiency is high. Therefore, the SAR image quality is reduced. Therefore, the utility model provides a six-rotor unmanned aerial vehicle-mounted 77GHz millimeter wave radar imaging device with a three-axis servo stability augmentation holder, which comprises a six-rotor unmanned aerial vehicle, a 77GHz millimeter wave radar and the three-axis servo stability augmentation holder. As the unmanned aerial vehicle platform and the millimeter-wave radar are connected and installed through the three-axis servo stability augmentation holder, the influence of the attitude change and the motion error of the six-rotor unmanned aerial vehicle platform on the millimeter-wave radar can be effectively reduced, the stability of the beam pointing of the millimeter-wave radar in the imaging process is ensured, and the purpose of improving the SAR imaging quality is further achieved.

The invention relates to a packaging structure of a micro display chip and a display device, and the packaging structure comprises a substrate, the surface of which comprises a display area and a non-display area; the electrode pads are located in the non-display area; and a plurality of through hole plugs located in the substrate, wherein one end of each through hole plug is electrically connected with the electrode pad. In AR near-to-eye display application, the light absorption structure can effectively absorb stray light returned from components such as an optical waveguide and the like, secondary specular reflection of the metal electrode pad on the non-display area is avoided, ghosting is prevented from being formed, and the imaging contrast ratio and the picture purity are remarkably improved. The light absorption structure is integrated in the packaging structure, and a stray light feedback path is cut off through a physical means on the premise that normal light emitting of a display area and electrical connection of an electrode pad are not affected, so that the optical performance of the micro-projection ray machine is improved, the final display effect is guaranteed, and the display effect is improved. Therefore, the technical problem of image quality degradation caused by high reflectivity of the non-display area is effectively solved.

The invention relates to a continuous zoom cycle-scan television system based on a zoom collimation scanning field lens structure and application thereof. Light reflected by a target image horizontally passes through the focusing group, the zooming group, the compensation group and the collimating field lens group in sequence along an optical axis, is obliquely reflected by 45 degrees by the galvanometer group and then vertically passes through the fixed group, is obliquely reflected by 45 degrees by the reflector group again and then horizontally passes through the optical filter switching group leftwards, and finally is imaged on a detector photosensitive surface of the high-definition imaging module; and the high-definition imaging module carries out photoelectric conversion and image processing and then outputs a high-definition video or image. According to the invention, the problem that the image quality is reduced during the swing scanning of the peripheral scanning television is solved, the turn-back of the light path is realized through the cooperation between the galvanometer group and the reflector group, and the galvanometer group rapidly swings the reflector to control the direction of the light beam to realize image motion compensation, so that the peripheral scanning detection function is realized. The system can be used for panoramic dead-corner-free monitoring and detailed reconnaissance of key targets, and is widely applied to the fields of intelligent monitoring, military reconnaissance, automatic driving and the like.

To provide a liquid dispensing device that can reduce the risk of degrading the image quality formed on the medium and the risk of impairing convenience. [Solution] A liquid dispensing device having a sink circuit that switches the impedance value between a first wiring through which a reference voltage signal supplied to the other end of a first piezoelectric element and the other end of a second piezoelectric element propagates, and a second wiring through which a signal with a lower potential than the reference voltage signal propagates, according to the determination result of the state of a plurality of dispensing units in a state determination circuit, the sink circuit having a first mode in which the impedance value is a first impedance value, a second mode in which the impedance value is a second impedance value smaller than the first impedance value, and a third mode in which the impedance value is a third impedance value smaller than the second impedance value.

The invention relates to the technical field of visual inspection, and discloses a machine vision intelligent detection device for automobile part production, which comprises a detection assembly, a mechanical arm, a mounting rack arranged on the mechanical arm, a shooting camera arranged in the mounting rack, a lens arranged on one side of the shooting camera, and a light source arranged at the bottom of the mounting rack. Through the arrangement of the cleaning assembly, when one side of the lens is in a standby state and is paused, the lens can be protected, so that the opportunity that dust falls on the surface of the lens can be reduced, the possibility that the image quality is reduced due to dust accumulation is reduced, and meanwhile, the lens is cleaned after being used for a certain time, so that the cleaning efficiency is improved. The cleaning period of each time is the same, so that unnecessary cleaning operation can be avoided, the physical structure and the optical performance of the camera are protected to the maximum extent, long-term stable work of the camera is ensured, and meanwhile it is ensured that the camera is not interfered by dust in the using process.

To provide an imaging device that suppresses deterioration in image quality due to difference (OB level difference) between an output of an OB region and that of an effective region.SOLUTION: When imaging sensitivity of an imaging element is changed in a third frame period between a first frame period and a second frame period, an imaging device corrects a first signal output from a first pixel using a second reference value obtained from a second signal output from a second pixel in a fourth frame period in each frame period from a fourth frame period after the third frame period to a fifth frame period when a second period longer than a frame period has elapsed. In a case where imaging sensitivity of the imaging element is not changed, in each frame period from a sixth frame period after the second frame period to a seventh frame period when the third period longer than the frame period has elapsed, a first signal output from the first pixel is corrected using a third reference value obtained from the second signal output from the second pixel in the sixth frame period.SELECTED DRAWING: Figure 5

The invention discloses an ultrasonic image processing method and an ultrasonic image processing device, and belongs to the field of medical image diagnos.The processing method comprises the following specific steps that P1, high-frequency and low-frequency ultrasonic waves are emitted through a dynamic frequency modulation probe, a composite ultrasonic image is constructed according to feedback ultrasonic signals, and then noise in the image is recognized and separated; according to the method, the final image can be ensured to have high resolution, low noise and high focus visibility, the diagnosis accuracy is improved, accurate focus identification and classification are realized, the reliability of clinical decision is improved, the image fusion quality is improved, and richer diagnosis information can be provided; the imaging quality of an operator is improved, the reduction of the image quality caused by manual operation errors is reduced, the stability and the repeatability of ultrasonic examination are improved, the method can adapt to different patients and different examination scenes, and the stability and the applicability of ultrasonic imaging are improved.

To propose the arrangement of column circuits for preventing a deterioration in image quality caused by the characteristic difference between pixel columns, the characteristic difference between pixel rows, color mixture, and a power supply variation.SOLUTION: A photoelectric conversion device has a pixel array including a plurality of pixels. A first pixel and a second pixel of the plurality of pixels correspond to different colors. The first pixel and a third pixel of the plurality of pixels correspond to the same color. The photoelectric conversion device has a first circuit group connected with the first pixel, and a third circuit group connected with the third pixel. The photoelectric conversion device has a first circuit included in the first circuit group, a second circuit, and a third circuit included in the third circuit group and having the same function as that of the first circuit. In a top view, the third circuit is arranged between the first circuit and the second circuit.SELECTED DRAWING: Figure 4

The invention provides a port container loading and unloading positioning method, system and equipment and a medium, and belongs to the technical field of port automation and machine vision positioning. The method comprises the following steps: acquiring a container surface image and synchronous sling motion data; the jitter amplitude is evaluated, the image is combined to analyze the illumination condition, and the multispectral image is adaptively selected or fused to generate an anti-interference image; angular point coordinates are extracted, the angular point coordinates and motion data are input into a vision-inertia tight coupling optimization model together for state estimation, and the real-time pose is solved; driving a lifting appliance-load dynamic model by using the motion data, and predicting pose deviation generated by inertia and swinging in the future; and the feedback control quantity based on the real-time pose and the feed-forward compensation quantity based on the prediction deviation are fused, and an accurate control instruction for driving the lifting appliance is generated. The problems of image quality degradation and feature loss caused by strong light, weak light and sling shaking are solved, and high-precision and high-robustness container positioning and alignment in a complex dynamic environment are achieved.

The invention relates to an in-area image acquisition device, which comprises a mounting box, and a first rotating shaft and a second rotating shaft which are rotatably connected to the mounting box, the lower end of the second rotating shaft is fixedly connected with a camera, the lens surface of the camera is rotatably connected with a third rotating shaft, and the third rotating shaft is fixedly connected with a dust removal plate. The side wall of the dust removal plate is attached to the surface of a lens of the camera, a first transmission assembly is arranged between the first rotating shaft and the third rotating shaft, the first transmission assembly can drive the third rotating shaft to rotate when the first rotating shaft rotates, and a first driving assembly used for driving the first rotating shaft to rotate is installed on the installation box. The invention aims to provide an intra-area image acquisition device so as to solve the problem that a lens of an image acquisition device is easy to be contaminated by dust due to exposure in air in the prior art. And the dust can scatter light rays, so that the quality of an image shot by the image acquisition equipment is reduced.

To suppress deterioration of image quality when dots are not formed due to factors such as clogging of a nozzle.SOLUTION: A printing apparatus acquires a position of a defective dot which is a pixel in which the dot cannot be formed by the head regardless of a position where the dot is formed, performs halftone processing of generating dot data indicating presence or absence of dot formation using image data including a plurality of pixels having a plurality of gradation values and a dither mask including a plurality of thresholds, searches for a threshold used in generation of a dot in a predetermined range in the vicinity of the defective dot, corrects a value of a changed threshold which is a threshold satisfying a search condition that the changed threshold is larger than a value of a target threshold which is a threshold used in the position of the defective dot to a value equivalent to the value of the target threshold, and performs the halftone processing in the pixel corresponding to the corrected threshold.SELECTED DRAWING: Figure 2

To provide a light-emitting body suppressing deterioration in image quality of an image imaged by an imaging device while suppressing enlargement of the light-emitting device even when a light emission part emitting invisible light such as IR light and a light emission part emitting visible light such as white light are incorporated into one light-emitting device.SOLUTION: A light-emitting device 1 is attached to a second support body supported by a first support body, and includes: a first light-emitting part 11a emitting invisible light detected by an imaging device 2 attached to the second support body; a second light-emitting part 11b emitting visible light; and a lens 20 through which the invisible light emitted from the first light-emitting part 11a and the visible light emitted from the second light-emitting part 11b transmits. An amount of light emitted from a part located on the side of the first support body in the lens 20 of the invisible light emitted from the first light-emitting part 11a is smaller than an amount of light emitted from a part located on the side opposite to the side of the first support body in the lens 20 of the invisible light emitted from the first light-emitting part 11a.SELECTED DRAWING: Figure 4

The invention discloses an archive digital image optimization sensitive information shielding system fused with image recognition, which relates to the technical field of image sensitive information shielding, and comprises an image shielding analysis module, a shielding effect analysis module and a final shielding effect evaluation module. A shielding strategy is dynamically selected based on the area proportion of the sensitive region: global shielding is carried out by adopting a chaotic mapping algorithm when the area is dense, a fine shielding matrix is generated through grid division when the area is sparse, and non-sensitive information is reserved to the maximum extent; a redundant region is positioned based on a shielding matrix accumulation algorithm, and the problem of image quality reduction caused by multi-region shielding overlapping is solved by combining sensitive type priority and attribution degree weight analysis; and moreover, the problems that a traditional method cannot dynamically select a shielding method according to the distribution of the sensitive areas and a normalized decision rule is lacked when multiple shielding matrixes conflict are solved, and the automation efficiency and the shielding accuracy of file digital processing are improved.

The invention provides a microscope video stream frame super-resolution method and system based on prediction assistance, and the method comprises the steps: carrying out the optical flow calculation of a historical frame, obtaining an initial optical flow, deducing the motion between a current frame and a future frame based on the initial optical flow, and obtaining a distorted optical flow and a propagation optical flow between the current frame and the future frame; calculating a motion vector field of pixels in the image of the current frame, and obtaining an estimated optical flow between the current frame and a future frame; obtaining a fusion optical flow field between the current frame and the future frame by combining the distorted optical flow, the propagated optical flow and the estimated optical flow from different sources; and based on the fused optical flow field, propagating image information of the current frame to a future frame through back propagation, and generating a target super-resolution frame through frame synthesis. According to the method, the phenomena of loss, jamming or freezing of the microscope video frame caused by bandwidth limitation, network delay or reduction of image quality are solved.

To provide an image forming method by which image quality is hardly deteriorated due to a difference in positional deviation when dots are formed.SOLUTION: An output image includes a first pixel group including a plurality of pixels whose positions in the output image are determined, and a second pixel group including a plurality of pixels whose positions are different from those of the pixels of the first pixel group. A halftone processing unit that performs halftone processing on an original image causes an arrangement of pixels where dots are formed in the first pixel group to have a distribution having a first characteristic relating to dispersibility, and in the second pixel group to have a distribution having a second characteristic relating to dispersibility and causes the distribution according to the second characteristic not to be correlated with the distribution according to the first characteristic when the input tone value of the original image is equal to or higher than an intermediate value. Then, the on / off of the dots in the arrangement having the first characteristic in the first pixel group is determined, and the on / off of the dots in the arrangement having the second characteristic in the second pixel group is determined.SELECTED DRAWING: Figure 16