WO2025224315A1

WO2025224315A1 - Circuitry and method for removing multipath-interference in time-of-flight signals using phase and confidence values

Info

Publication number: WO2025224315A1
Application number: PCT/EP2025/061369
Authority: WO
Inventors: Kotaro SONODA; Jean Louis NICKS; Jernej PERHAVC
Original assignee: Sony Depthsensing Solutions NV SA; Sony Semiconductor Solutions Corp
Current assignee: Sony Depthsensing Solutions NV SA; Sony Semiconductor Solutions Corp
Priority date: 2024-04-26
Filing date: 2025-04-25
Publication date: 2025-10-30
Anticipated expiration: 2026-10-26

Abstract

Demodulation values according to the present disclosure may refer to values based on which a distance can be determined, such as I-values and Q-values, as commonly known in the field of indirect time-of-flight depth sensing. According to the present disclosure, first a phase value and a confidence value may be obtained from raw data (e.g., tap signal) in order to obtain the demodulation values. The phase value and the confidence value may correspond to a polar coordinate display of the I- and Q-value. I and Q according to the present disclosure may be named pseudo-IQ since they are not directly derived from tap values, but instead, are determined based on phase and confidence, i.e. phase and confidence are obtained before I and Q are generated. This is due to the application of Hamiltonian coding in the present disclosure which gives as a result a phase value and a confidence value. In order to remove multipath-interference (MPI) of a time-of flight signal with direct-global separation (DGS), phase and confidence may not be useful and instead, I and Q may be used as an input to a DGS algorithm, such that the pseudo-IQ values (i.e., at least two demodulation values) are used for that. Hence, in some embodiments, an influence of MPI on resulting ToF data is removed based on the at least two demodulation values.

Description

CIRCUITRY AND METHOD FOR REMOVING MULTIPATH-INTERFERENCE IN TIME-OF-FLIGHT SIGNALS USING PHASE AND CONFIDENCE VALUES

TECHNICAL FIELD

The present disclosure generally pertains to time-of-flight circuitry and a time-of-flight method.

TECHNICAL BACKGROUND

It is generally known that lower phase noise may be achieved by properly designing depth coding functions (e.g., Hamiltonian coding) that create longer depth coding curves for indirect time-of-flight (iToF) depth sensing systems..

Moreover, direct-global separation (DGS) may be known as a method that processes I and Q values and reduces phase error and noise caused by multipath interference for conventional iToF systems operated with continuous wave coding schemes. In more general terms, DGS may separate direct and global components of a signal

Although there exist techniques for obtaining a depth image, it is generally desirable to provide time-of-flight circuitry and a time-of-flight method.

SUMMARY

According to a first aspect, the disclosure provides time-of-flight circuitry configured to: generate, based on an obtained phase value and an obtained confidence value, at least two demodulation values; and remove, based on the at least two demodulation values, an influence of multipathinterference on resulting time-of-flight data.

According to a second aspect, the disclosure provides a time-of-flight method comprising: generating, based on an obtained phase value and an obtained confidence value, at least two demodulation values; and removing, based on the at least two demodulation values, an influence of multipathinterference on resulting time-of-flight data.

Further aspects are set forth in the dependent claims, the drawings and the following description.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments are explained by way of example with respect to the accompanying drawings, in which:

Fig. 1 depicts exemplary timing diagrams of a continuous wave coding scheme; Fig. 2 depicts an embodiment of timing diagrams of a Hamiltonian coding scheme;

Fig. 3 depicts a data path (top) according to the present disclosure and a diagram for converting phase and confidence into pseudo-IQ values (bottom);

Fig. 4 depicts an experimental setup to evaluate the effects of the present disclosure;

Fig. 5 depicts the results of the experiments of Fig. 4;

Fig. 6 depicts further results of the present disclosure;

Fig. 7 depicts block diagram of a time-of-flight method according to the present disclosure;

Fig. 8 depicts a further block diagram of a time-of-flight method according to the present disclosure in which spot ToF is used and tap values are denoised; and

Fig. 9 depicts an embodiment of a ToF imaging apparatus according to the present disclosure.

DETAILED DESCRIPTION OF EMBODIMENTS

Before a detailed description of the embodiments under reference of Fig. 2 is given, general explanations are made.

As mentioned in the outset, Hamiltonian coding is generally known for iToF as a depth coding method to achieve low phase noise. However, it has been recognized that an influence of multipath interference (MPI) (e.g., a phase error) may be reduced or removed when direct-global separation (DGS) is applied, which is, however, only known for spot ToF (e.g., spot iToF) with conventional coding patterns (e.g., continuous wave coding or other non-Hamiltonian coding schemes). Spot ToF may be known as a technique in which light spots are emitted and a depth image is measured/detected/processed based on the light spots. Furthermore, in DGS, valley pixel information (pixels in which no reflected light spot is measured/detected/processed) is used for an interpolation and for subtracting a global component that carries information indicative of the MPI in order to extract (only) direct components in the illuminated pixels. Hence, the present disclosure provides Hamiltonian coding for a spot ToF system. For further information on DGS, please refer to patent application publication WO 2019/215172 Al, which is hereby incorporated by reference.

However, for conventional DGS methods used in the context of iToF (with non-Hamiltonian coding), IQ values (I = in-phase components; Q = quadrature components), which are respectively the real and the imaginary part of a phasor plot, are needed as a minimum input, whereas Hamiltonian coding directly provides phase and confidence without the need to compute IQ values. It has been recognized that pseudo-IQ values may be generated based on that information, such that according to the present disclosure, DGS may be applied to a Hamiltonian coding spot ToF system. In other words, the derivation of pseudo-IQ values from phase a confidence enables DGS to be applied to Hamiltonian coding, thus providing results with relatively lower noise and multipath interference.

Therefore, some embodiments pertain to time-of-flight circuitry configured to: generate, based on an obtained phase value and an obtained confidence value, at least two demodulation values; and remove, based on the at least two demodulation values, an influence of multipathinterference on resulting time-of-flight data.

Circuitry may pertain to any entity or multitude of entities configured to generate signals in order to control a time-of-flight camera, such as a CPU (central processing unit), GPU (graphics processing unit), FPGA (field-programmable gate array), or the like. Also, combinations of these entities may be envisaged, in some embodiments.

In some embodiments, demodulation values may be generated based on an obtained phase value and an obtained confidence value.

Demodulation values according to the present disclosure may refer to values based on which a distance can be determined, such as Lvalues and Q-values, as commonly known in the field of indirect time-of-flight depth sensing. According to the present disclosure, first a phase value and a confidence value may be obtained from raw data (e.g., tap signal) in order to obtain the demodulation values. The phase value and the confidence value may correspond to a polar coordinate display of the I- and Q-value. However, since in commonly known indirect time-of- flight, I and Q are obtained before the phase and the confidence are determined, I and Q according to the present disclosure may be named pseudo-IQ since they are not directly derived from tap values, but instead, are determined based on phase and confidence.

As mentioned above, phase and confidence are obtained before I and Q are generated. This is due to the application of Hamiltonian coding in the present disclosure which gives as a result a phase value and a confidence value.

However, it has been recognized that, in order to remove multipath-interference (MPI) of a time- of-flight signal with direct-global separation (DGS), phase and confidence may not be useful and instead, I and Q may be used as an input to a DGS algorithm, such that the pseudo-IQ values (i.e., at least two demodulation values) are used for that. Hence, in some embodiments, an influence of MPI on resulting ToF data is removed based on the at least two demodulation values.

In some embodiments, the removal of the influence of the MPI is carried out based on a function that accepts the at least two demodulation values, such as a DGS algorithm. As indicated above, pseudo-IQ values may be used as the at least two demodulation values.

In some embodiments, the influence of the multipath-interference is carried out based on direct- global separation, as discussed herein.

In some embodiments, the removal of the influence of the multipath-interference is carried out based on valley pixel information and dot pixel information.

For example, the removal is carried out based on an interpolation based on the valley pixel information. Thereby, an influence of MPI on measured phase may be reduced or removed. Multipath interference may be caused, for example, by internal scattering (e.g. bouncing between internal elements such as lenses and sensor) and external scattering (e.g., sub-surface scattering, multiple bouncing at comer, etc.). In one example, the suppression or removal of the MPI by the DGS algorithm is carried out through multiple steps. Dot positions (i.e., illuminated areas on the sensor) and valley positions that are not directly illuminated by the active light are identified on a pixel level from an intensity image or confidence image in order to create an image mask through a local-maxima search. The image mask can exclusively extract valley information or dot information in I and Q images. By applying the mask and interpolation, inpainted images of I and Q including only valley information (i.e., global component) are obtained. The inpainting algorithm may be based on, for example, nearest neighbors, linear interpolation, sparse representation, artificial neural network, and so on. Subtracting the aforementioned inpainted IQ images from the original IQ and applying the mask results in MPI-free images of I and Q where only a direct component on the dot positions exists.

In some embodiments, the obtained phase value and the obtained confidence value are obtained based on Hamiltonian coding, as discussed herein, for example through a phase decoder that is designed for the Hamiltonian coding scheme.

In some embodiments, Hamiltonian coding is based on a correlation signal that satisfies characteristics of a Hamiltonian cycle. In other words, Hamiltonian coding may refer to a depth coding method that is based on a correlation signal that satisfies characteristics of a Hamiltonian cycle. A Hamiltonian coding curve may correspond to a cycle graph along a hypercube, where each orthogonal axis spanning the N-dimensional space corresponds to the value of the i-th component (i=0, 1, 2, ... N-l) of the correlation signals obtained from mix and illumination signals. The Hamiltonian coding curve may satisfy fundamental characteristics of a Hamiltonian cycle (i.e., visiting each vertex of the hypercube only once in a single cycle). Only one signal component of the correlation signal may change in a specific region at the same time. As long as this condition is satisfied, any indirect-ToF system (e.g., different devices, different operating modes, different number of taps, different number of components, and so on) may be used for the implementation of the present disclosure.

In general terms, a Hamiltonian coding curve may refer to a correlation signal (or multiple correlation signals) in which, when one signal component changes, the other signal components are kept constant during the change of the one component.

In the present disclosure, the Hamiltonian coding and other similar depth coding families that are based on an idea of maximizing the length of the coding curve, such as Hilbert coding, Hamiltonian-based Gray coding, their derivatives, and so on, may be also considered and be referred to as the Hamiltonian coding for the sake of simplicity. These coding families utilize a functional block called a decoder to extract phase from a long coding curve and do not directly provide I and Q values.

On the other hand, the definition of non-Hamiltonian coding schemes includes conventional depth coding methods for iToF depth sensing systems using, for example, square wave, sinusoidal wave, and other widely-used waves of signals, which may typically rely on I and Q values for calculating phase.

According to the present disclosure, a decoder may include any function that converts raw or filtered tap values to raw phases. There are several decoders that may be defined, such as an analytical expression, a look-up table, statistical processing, geometry processing, graph processing, and any other mathematical methods. For example, the decoder may first determine a region (i.e., roughly on which edge a target is positioned on a hypercube). Using geometrical characteristics of signals derived from tap values (called region signals), a precise position is determined with the decoder.

Hamiltonian confidence may be defined in various ways, but may be different from conventional iToF where the confidence is determined from I and Q values. Since only tap values may be available in Hamiltonian coding, the confidence may be derived from tap values. In the Hamiltonian coding scheme, confidence may be related to the amount of the active light received by the sensor. In one example, the largest absolute difference of two components (component[i]=tapA[i]-tapB[i], where i = 0, 1, 2, and 3 in the case of two-tap and four- component iToF) is defined as confidence, i.e., max(|component[i] - component[j]|), where i and j are integers and not the same, because it may correspond to the amount of signal from the active light. Additional statistical calculations, e.g., averaging two largest signal values, may be also considered. It should be noted that the present disclosure is not limited to the example described above (two-tap, four component iToF and the skilled person may apply the principles of the present disclosure to more component iToF systems, as well).

Fig. 1 depicts exemplary timing diagrams 1, 2, and 3 of different signals of a continuous wave scheme in conventional iToF (indirect time-of-flight) which is based on four-component and two-tap iToF. Timing diagram 1 depicts an illumination signal, i.e., a signal that is applied to a light source. The illumination signal includes four phase-shifted sub-signals that are applied to different elements of the light source and, wherein the sub-signals are phase-shifted by ninety degrees. Timing diagram 2 depicts a mix signal with four sub-signals that are applied to a sensor and that are each the same. Timing diagram 3 depicts a correlation signal which is used to read out pixels on which the reflected light is incident.

However, such a continuous wave scheme results in a shorter coding curve than what can be achieved with the Hamiltonian coding. Because of that, a continuous wave scheme may have more phase noise. An embodiment of a Hamiltonian coding scheme is briefly described under reference of Fig. 2, wherein it should be noted that the present disclosure is not limited to any specific signals as long as the condition is fulfilled that a Hamiltonian cycle is satisfied, as discussed herein.

Fig. 2 depicts an embodiment of timing diagrams 10, 11, and 12. Timing diagram 10 depicts the illumination signal. Timing diagram 11 depicts the mix signal. The temporal profiles of the illumination 10 and mix signals 11 are one of possible examples based on a two-tap and four- component iToF depth-sensing system. The actual shapes and number of the correlation signals may differ and be determined by considering hardware specification (e.g., available power budget, sensor, laser driver, clock settings, and so on) and target applications. The illumination and mix signals are designed to generate correlation signals that can satisfy the characteristics of the Hamiltonian coding. Timing diagram 12 depicts the correlation signal. As mentioned above, only one signal component changes at the same time while the other signal components are kept constant during the change of the one signal component.

In some embodiments, the circuitry is further configured to: apply a spot illumination scheme for obtaining the phase value and the confidence value.

In some embodiments, the obtained phase value and the obtained confidence value are obtained based on at least two tap values, as discussed herein.

In some embodiments, the circuitry is further configured to: apply a denoising filter to the at least two tap values, e.g., before obtaining the phase and the confidence. Thereby, a result may further be enhanced.

Some embodiments pertain to a time-of-flight method including: generating, based on an obtained phase value and an obtained confidence value, at least two demodulation values; and removing, based on the at least two demodulation values, an influence of multipath-interference on resulting time-of-flight data, as discussed herein.

The method may be carried out with circuitry according to the present disclosure.

In some embodiments, the removal of the influence of the multipath-interference is carried out based on a function that accepts the at least two demodulation values, as discussed herein. In some embodiments, the removal of the influence of the multipath-interference is carried out based on direct-global separation, as discussed herein. In some embodiments, the removal of the influence of the multipath-interference is carried out based on valley pixel information and dot pixel information, as discussed herein. In some embodiments, the removal is carried out based on an interpolation based on the valley pixel information, as discussed herein. In some embodiments, the obtained phase value and the obtained confidence value are obtained based on Hamiltonian coding, as discussed herein. In some embodiments, Hamiltonian coding is based on a correlation signal that satisfies characteristics of a Hamiltonian cycle, as discussed herein. In some embodiments, the method further includes: applying a spot illumination scheme for obtaining the phase value and the confidence value, as discussed herein. In some embodiments, the obtained phase value and the obtained confidence value are obtained based on at least two tap values, the method further includes: applying a denoising filter to the at least two tap values, as discussed herein.

The methods as described herein are also implemented in some embodiments as a computer program causing a computer and/or a processor to perform the method, when being carried out on the computer and/or processor. In some embodiments, also a non-transitory computer- readable recording medium is provided that stores therein a computer program product, which, when executed by a processor, such as the processor described above, causes the methods described herein to be performed.

Fig. 3 depicts a method or a data path 20 (top) and an illustrational diagram 30 on how to obtain or derive pseudo-IQ values from phase and confidence (bottom).

In the data path 20, at 21, tap values (Tap A and Tap B, for example) are obtained as a result of Hamiltonian coding with spot ToF.

At 22 and 23, based on the obtained tap values, a phase value (at 22) and a confidence value (at 23) are generated.

The phase value and the confidence value are a polar coordinate expression of pseudo-IQ values, as depicted in the diagram 30. The confidence is the amplitude of the depicted point and the phase is its angle with respect to the F (pseudo-I) axis. Accordingly, F and Q’ may be calculated as:

I’ = cos(cp)*C

Q’ = sin(cp)*C wherein C is the confidence and <p is the phase.

Accordingly, at 24, 1’ and Q’ (i.e., pseudo-IQ) are determined.

At 25, the pseudo-IQ values are fed into a direct-global separation (DGS) algorithm, thereby an influence of MPI is removed. At 26, resulting values (IQ DGS) are re-transformed into a DGS phase value which does not include the influence of MPI anymore.

Fig. 4 depicts an example of an experimental setup 40 to evaluate the effects of the present disclosure (which are then discussed under reference of Fig. 5). An active illuminator 41 (e.g., a laser) is directed onto a flat white panel 42. Behind the panel 42, a flat checkerboard 43 is arranged as a main target. The checkerboard 43 has high- and low-reflectivity areas in an alternating fashion. The panel 42 is arranged in a way that a lower part of a field-of-view of a receiver 44 is covered. In order to simulate MPI, the receiver 44 (e.g., lenses and sensor) is provided next to the active illuminator 41, such that a part of the light that is emitted from the active illuminator 41 is redirected to the checkerboard 43. The active illuminator 41 and the receiver 44 may constitute a time-of-flight camera. Hence, it is expected that the active illuminator 41 receives reflected light from the sheet of paper 42 and reflected light from the checkerboard 43.

In other words, The active light reflected from a white area of the checkerboard 43 may be dominantly detected by some pixels of the receiver 44. However, if the active light hits to a black area (i.e., a low-reflectivity area) of the checkerboard 43, a global component 46 originating from strong internal scattering in the receiver 44 may have non-negligible contribution to a detected signal on a single pixel compared to a direct component 45. As a result, phase shift due to MPI may be observed.

Fig. 5 depicts results of the experiment when different illumination patterns and coding schemes are applied in experimental setup of Fig. 4. In Fig. 5, the y-axis represents an uncalibrated raw phase of the flat checkerboard 43 at a specific row and the x-axis represents a horizontal pixel number.

The top two diagrams are obtained with continuous wave coding/demodulation and the bottom two diagrams are obtained with Hamiltonian coding. Moreover, the two left diagrams are obtained based on a full field illumination and the two right diagrams are obtained with a spot illumination (also referred to as “dot illumination”, in some embodiments - it should be noted that in the present disclosure, the terms dot and spot may be used interchangeably) and subsequent application of DGS.

The top left diagram (continuous wave and full field illumination) depicts a rather noisy image in which the checkerboard pattern (i.e., the influence of the MPI) is visible.

In the bottom left diagram (Hamiltonian coding and full field illumination), the results are not as noisy as in the top left diagram and the resulting curve is more pronounced, i.e., the resolution is improved. However, the checkerboard pattern is still visible, i.e., the influence of MPI is not removed.

In the top right diagram (continuous wave and spot illumination with DGS), the checkerboard pattern is not visible anymore, i.e., the influence of MPI is removed, but compared to the bottom right diagram, the results are subject to more noise.

In the bottom right diagram (Hamiltonian coding and spot illumination with DGS), the noise is minimal, the resolution is enhanced, and the checkerboard pattern is not visible, i.e., the influence of MPI is removed. Fig. 6 depicts further results of the present disclosure. On the left, a top-view of a ground truth depth of a corner is depicted (with thick lines) which should be captured with a ToF camera. However, as can be seen from the rounded dashed line around the corner, the result (measured depth) is subject to noise and MPI. When the present disclosure is applied (on the right), the dashed line becomes the shape of the corner.

Fig. 7 depicts a time-of-flight method 50 according to the present disclosure.

At 51, at least two demodulation values are generated based on an obtained phase value and an obtained confidence value, as discussed herein.

At 52, an influence of MPI is removed based on the at least two demodulation values.

Fig. 8 depicts a time-of-flight method 60 according to the present disclosure.

At 61, a spot illumination is applied, as discussed herein.

At 62, obtained tap values are denoised with a denoising filter.

At 63, at least two demodulation values are generated based on an obtained phase value and an obtained confidence value, as discussed herein.

At 64, an influence of MPI is removed based on the at least two demodulation values.

Referring to Fig. 9, there is illustrated an embodiment of a time-of-flight (ToF) imaging apparatus 70, which can be used for depth sensing or providing a distance measurement, in particular for the technology as discussed herein, wherein the ToF imaging apparatus 70 is configured as a spot ToF camera. The ToF imaging apparatus 70 has time-of-flight circuitry 77, which is configured to perform the methods as discussed herein and which forms a control of the ToF imaging apparatus 70 (and it includes, not shown, corresponding processors, memory and storage, as it is generally known to the skilled person).

The ToF imaging apparatus 70 has a modulated light source 71 configured to apply spot ToF and it includes light emitting elements (based on laser diodes), wherein in the present embodiment, the light emitting elements are narrow band laser elements.

The light source 71 emits spot-patterned light which is temporally modulated, as discussed herein, to a scene 72 (region of interest (ROI) or object), which reflects the light. The reflected light is focused by an optical stack 73 to a light detector 74.

The light detector 74 has a time-of-flight imaging portion, which is implemented based on multiple CAPDs (current assisted photonic demodulators) formed in an array of pixels and a micro lens array 76 which focuses the light reflected from the scene 72 to the time-of-fhght imaging portion 75 (to each pixel of the image sensor 75).

The light emission time and modulation information is fed to the time-of-flight circuitry or control 77 including a time-of-flight measurement unit 78, which also receives respective information from the time-of-flight imaging portion 75, when the light is detected which is reflected from the scene 72. On the basis of the modulated light received from the light source 71, the time-of-flight measurement unit 78 applies a data path as discussed under reference of Fig. 3 and computes a DGS phase of the received modulated light which has been emitted from the light source 71 and reflected by the scene 72 and on the basis thereon it computes a distance d (depth information) between the image sensor 75 and the scene 72.

The depth information is fed from the time-of-flight measurement unit 79 to a 3D image reconstruction unit 79 of the time-of-flight image sensor circuitry 77, which reconstructs (generates) a 3D image of the scene 72 based on the depth data.

The present disclosure may be applied to any ToF system which uses spot illumination, which can generate a Hamiltonian coding curve, and which uses an appropriate decoder (i.e., tap-to- phase converter), such as any indoor use case that relies on 3D information (e.g., spatial video, augmented reality, virtual reality, simultaneous localization and mapping, 3D capture, digital bokeh, etc.) and on light-matter interaction (e.g., material sensing).

It should be recognized that the embodiments describe methods with an exemplary ordering of method steps. The specific ordering of method steps is however given for illustrative purposes only and should not be construed as binding. Changes of the ordering of method steps may be apparent to the skilled person.

Please note that the division of the control 77 into units 78 and 79 is only made for illustration purposes and that the present disclosure is not limited to any specific division of functions in specific units. For instance, the control 77 could be implemented by a respective programmed processor, field programmable gate array (FPGA) and the like.

The method discussed herein can also be implemented as a computer program causing a computer and/or a processor to perform the method, when being carried out on the computer and/or processor. In some embodiments, also a non-transitory computer-readable recording medium is provided that stores therein a computer program product, which, when executed by a processor, such as the processor described above, causes the method described to be performed. All units and entities described in this specification and claimed in the appended claims can, if not stated otherwise, be implemented as integrated circuit logic, for example on a chip, and functionality provided by such units and entities can, if not stated otherwise, be implemented by software.

In so far as the embodiments of the disclosure described above are implemented, at least in part, using software-controlled data processing apparatus, it will be appreciated that a computer program providing such software control and a transmission, storage or other medium by which such a computer program is provided are envisaged as aspects of the present disclosure.

Note that the present technology can also be configured as described below.

(1) Time-of-flight circuitry configured to: generate, based on an obtained phase value and an obtained confidence value, at least two demodulation values; and remove, based on the at least two demodulation values, an influence of multipathinterference on resulting time-of-flight data.

(2) The time-of-flight circuitry of (1), wherein the removal of the influence of the multipathinterference is carried out based on a function that accepts the at least two demodulation values.

(3) The time-of-flight circuitry of (1) or (2), wherein the removal of the influence of the multipath-interference is carried out based on direct-global separation.

(4) The time-of-flight circuitry of anyone of (1) to (3), wherein the removal of the influence of the multipath-interference is carried out based on valley pixel information and dot pixel information.

(5) The time-of-flight circuitry of (4), wherein the removal is carried out based on an interpolation based on the valley pixel information.

(6) The time-of-flight circuitry of anyone of (1) to (5), wherein the obtained phase value and the obtained confidence value are obtained based on Hamiltonian coding.

(7) The time-of-flight circuitry of (6), wherein Hamiltonian coding is based on a correlation signal that satisfies characteristics of a Hamiltonian cycle.

(8) The time-of-flight circuitry of anyone of (1) to (8), further configured to: apply a spot illumination scheme for obtaining the phase value and the confidence value.

(9) The time-of-flight circuitry of anyone of (1) to (8), wherein the obtained phase value and the obtained confidence value are obtained based on at least two tap values. (10) The time-of-flight circuitry of (9), further configured to: apply a denoising filter to the at least two tap values.

(11) A time-of-flight system comprising: time-of-flight circuitry according to anyone of (1) to (10) and; an active illuminator configured to emit modulated light according to a spot illumination.

(12) A time-of-flight method comprising: generating, based on an obtained phase value and an obtained confidence value, at least two demodulation values; and removing, based on the at least two demodulation values, an influence of multipathinterference on resulting time-of-flight data.

(13) The time-of-flight method of (12), wherein the removal of the influence of the multipathinterference is carried out based on a function that accepts the at least two demodulation values.

(14) The time-of-flight method of (12) or (13), wherein the removal of the influence of the multipath-interference is carried out based on direct-global separation.

(15) The time-of-flight method of anyone of (12) to (14), wherein the removal of the influence of the multipath-interference is carried out based on valley pixel information and dot pixel information.

(16) The time-of-flight method of (15), wherein the removal is carried out based on an interpolation based on the valley pixel information.

(17) The time-of-flight method of anyone of (12) to (16), wherein the obtained phase value and the obtained confidence value are obtained based on Hamiltonian coding.

(18) The time-of-flight method of (17), wherein Hamiltonian coding is based on a correlation signal that satisfies characteristics of a Hamiltonian cycle.

(19) The time-of-flight method of anyone of (12) to (18), further comprising: applying a spot illumination scheme for obtaining the phase value and the confidence value.

(20) The time-of-flight method of anyone of (12) to (19), wherein the obtained phase value and the obtained confidence value are obtained based on at least two tap values.

(21) The time-of-flight method of (20), further comprising: applying a denoising filter to the at least two tap values. (22) A computer program comprising program code causing a computer to perform the method according to anyone of (12) to (21), when being carried out on a computer.

(23) A non-transitory computer-readable recording medium that stores therein a computer program product, which, when executed by a processor, causes the method according to anyone of (12) to (21) to be performed.

Claims

1. Time-of-flight circuitry configured to: generate, based on an obtained phase value and an obtained confidence value, at least two demodulation values; and remove, based on the at least two demodulation values, an influence of multipathinterference on resulting time-of-flight data.

2. The time-of-flight circuitry of claim 1, wherein the removal of the influence of the multipath-interference is carried out based on a function that accepts the at least two demodulation values.

3. The time-of-flight circuitry of claim 1, wherein the removal of the influence of the multipath-interference is carried out based on direct-global separation.

4. The time-of-flight circuitry of claim 1, wherein the removal of the influence of the multipath-interference is carried out based on valley pixel information and dot pixel information.

5. The time-of-flight circuitry of claim 4, wherein the removal is carried out based on an interpolation based on the valley pixel information.

6. The time-of-flight circuitry of claim 1, wherein the obtained phase value and the obtained confidence value are obtained based on Hamiltonian coding.

7. The time-of-flight circuitry of claim 6, wherein Hamiltonian coding is based on a correlation signal that satisfies characteristics of a Hamiltonian cycle.

8. The time-of-flight circuitry of claim 1, further configured to: apply a spot illumination scheme for obtaining the phase value and the confidence value.

9. The time-of-flight circuitry of claim 1, wherein the obtained phase value and the obtained confidence value are obtained based on at least two tap values.

10. The time-of-flight circuitry of claim 9, further configured to: apply a denoising filter to the at least two tap values.

11. A time-of-flight method comprising: generating, based on an obtained phase value and an obtained confidence value, at least two demodulation values; and removing, based on the at least two demodulation values, an influence of multipathinterference on resulting time-of-flight data.

12. The time-of-flight method of claim 11, wherein the removal of the influence of the multipath-interference is carried out based on a function that accepts the at least two demodulation values.

13. The time-of-flight method of claim 11, wherein the removal of the influence of the multipath-interference is carried out based on direct-global separation.

14. The time-of-flight method of claim 11, wherein the removal of the influence of the multipath-interference is carried out based on valley pixel information and dot pixel information.

15. The time-of-flight method of claim 14, wherein the removal is carried out based on an interpolation based on the valley pixel information.

16. The time-of-flight method of claim 11, wherein the obtained phase value and the obtained confidence value are obtained based on Hamiltonian coding.

17. The time-of-flight method of claim 16, wherein Hamiltonian coding is based on a correlation signal that satisfies characteristics of a Hamiltonian cycle.

18. The time-of-flight method of claim 11, further comprising: applying a spot illumination scheme for obtaining the phase value and the confidence value.

19. The time-of-flight method of claim 11, wherein the obtained phase value and the obtained confidence value are obtained based on at least two tap values.

20. The time-of-flight method of claim 19, further comprising: applying a denoising filter to the at least two tap values.