US-12626344-B2 - Image processor and image processing system including the same

US12626344B2US 12626344 B2US12626344 B2US 12626344B2US-12626344-B2

Abstract

Disclosed is an image processor and an image processing system including the same. The image processor includes an analyzer configured to generate quantified characteristic values of noise reflected in a captured image based on image values corresponding to the captured image, and a discriminator configured to determine whether the noise has occurred in the captured image based on the characteristic values.

Inventors

Ji Hee HAN

Assignees

SK Hynix Inc.

Dates

Publication Date: 20260512
Application Date: 20240201
Priority Date: 20230831

Claims (20)

1 . An image processor comprising: an analyzer configured to generate quantified characteristic values of noise reflected in a captured image based on image values corresponding to the captured image; and a discriminator configured to determine whether the noise has occurred in the captured image based on the characteristic values, wherein the analyzer includes: a noise extractor configured to extract the noise based on the image values; an edge extractor configured to extract edge components from the noise; and an edge analyzer configured to generate the characteristic values based on the edge components and the image values.
2 . The image processor of claim 1 , wherein the analyzer is configured to extract the noise by excluding data components from the image values, and generate the characteristic values based on the noise.
3 . The image processor of claim 1 , wherein the discriminator is configured to generate another characteristic values based on threshold values that vary according to intensity of a value corresponding to the image values.
4 . The image processor of claim 1 , wherein the noise extractor includes: an image interpolator configured to interpolate the image values; an image converter configured to convert the interpolated image values into gray image values; a noise filter configured to filter the gray image values, and generate filtered image values corresponding to data components by excluding noise components from the gray image values; and a data remover configured to remove the data components from the gray image values based on the filtered image values and the gray image values.
5 . The image processor of claim 4 , wherein the data remover is configured to model the noise remaining after the data components are removed from the gray image values, by normalizing the filtered image values.
6 . The image processor of claim 1 , wherein the edge analyzer includes: a region divider configured to define the captured image as one region or divide the captured image into at least two regions, and generate at least one average image value of the at least one region, based on the image values; a region selector configured to select a region of interest from the one region or the at least two regions based on the at least one average image value; and a calculator configured to calculate the characteristic values corresponding to the region of interest based on the edge components.
7 . The image processor of claim 6 , wherein the calculator is configured to calculate the characteristic values by multiplying the edge components by a predetermined constant number.
8 . The image processor of claim 1 , wherein the characteristic values include a first gradient score corresponding to a noise component of a vertical direction, a second gradient score corresponding to a noise component of a horizontal direction, and a third gradient score corresponding to a difference between the first gradient score and the second gradient score.
9 . An image processing system comprising: an image sensor configured to generate image values corresponding to a captured image; and an image processor configured to model noise independent of data components and quantify the noise, based on the image values, wherein the image processor includes: an analyzer configured to generate quantified characteristic values of the noise reflected in the captured image based on the image values; and a discriminator configured to qualitatively and quantitatively evaluate the noise based on the characteristic values, and wherein the analyzer includes: a noise extractor configured to extract the noise based on the image values; an edge extractor configured to extract edge components from the noise; and an edge analyzer configured to generate the characteristic values based on the edge components and the image values.
10 . The image processing system of claim 9 , wherein the image processor is configured to quantify edge components of the noise.
11 . The image processing system of claim 9 , wherein the analyzer is configured to extract the noise by excluding the data components from the image values and generate the characteristic values based on the noise.
12 . The image processing system of claim 9 , wherein the discriminator is configured to generate another characteristic value based on threshold values that vary according to intensity of a value corresponding to the image values.
13 . The image processing system of claim 9 , wherein the noise extractor includes: an image interpolator configured to interpolate the image values; an image converter configured to convert the interpolated image values into gray image values; a noise filter configured to filter the gray image values, and generate filtered image values corresponding to data components excluding noise components from the gray image values; and a data remover configured to remove the data components from the gray image values based on the filtered image values and the gray image values.
14 . The image processing system of claim 13 , wherein the data remover is configured to model the noise remaining after the data components are removed from the gray image values, by normalizing the filtered image values.
15 . The image processing system of claim 9 , wherein the edge analyzer includes: a region divider configured to define the captured image as one region or divide the captured image into at least two regions, and generate at least one average image value of the at least one region, based on the image values; a region selector configured to select a region of interest from the one region or the at least two regions based on the at least one average image value; and a calculator configured to calculate the characteristic values corresponding to the region of interest based on the edge components.
16 . The image processing system of claim 15 , wherein the calculator is configured to calculate the characteristic values by multiplying the edge components by a predetermined constant number.
17 . The image processing system of claim 9 , wherein the characteristic values include a first gradient score corresponding to a noise component of a vertical direction, a second gradient score corresponding to a noise component of a horizontal direction, and a third gradient score corresponding to a difference between the first gradient score and the second gradient score.
18 . An image processing method comprising: generating image values corresponding to a captured image; extracting noise reflected in a captured image based on the image values; extracting edge components from the noise; generating quantified characteristic values of the noise based on the edge components and the image values; and qualitatively and quantitatively evaluating the noise based on the characteristic values.
19 . The image processing method of claim 18 , wherein the extracting of the noise comprises: interpolating the image values; converting the interpolated image values into gray image values; filtering the gray image values; generating filtered image values corresponding to data components by excluding noise components from the gray image values; removing the data components from the gray image values based on the filtered image values and the gray image values; and modeling the noise remaining after the data components are removed from the gray image values, by normalizing the filtered image values.
20 . The image processing method of claim 18 , wherein the generating of the characteristic values comprises: dividing the captured image into at least two regions and generating at least two average image values of the at least two regions, based on the image values; selecting a region of interest from the at least two regions based on the at least two average image values; and calculating the characteristic values corresponding to the region of interest based on the edge components.

Description

CROSS-REFERENCE TO RELATED APPLICATION(S) This application claims priority under 35 U.S.C. § 119 to Korean Patent Application No. 10-2023-0115485, filed on Aug. 31, 2023, the disclosure of which is incorporated herein by reference in its entirety. BACKGROUND 1. Field Various embodiments of the present disclosure relate to a semiconductor design technique, and more particularly, to an image processor and an image processing system including the same. 2. Description of the Related Art Image sensors are devices for capturing images using the property of a semiconductor which reacts to light. Image sensors may be roughly classified into charge-coupled device (CCD) image sensors and complementary metal-oxide semiconductor (CMOS) image sensors. Recently, CMOS image sensors are widely used because the CMOS image sensors can allow both analog and digital control circuits to be directly implemented on a single integrated circuit (IC). As the image sensors become more highly integrated and faster, the image sensors become more susceptible to noise, and images captured through the image sensors may deteriorate due to the noise. SUMMARY Various embodiments of the present disclosure are directed to an image processor capable of evaluating noise qualitatively and quantitatively, and an image processing system including the image processor. In accordance with an embodiment of the present disclosure, an image processor may include: an analyzer configured to generate quantified characteristic values of noise reflected in a captured image based on image values corresponding to the captured image; and a discriminator configured to determine whether the noise has occurred in the captured image based on the characteristic values. In accordance with an embodiment of the present disclosure, an image processing system may include: an image sensor configured to generate image values corresponding to a captured image; and an image processor configured to model noise independent of data components and quantify the noise, based on the image values. In accordance with an embodiment of the present disclosure, an image processing method may include: generating image values corresponding to a captured image; extracting noise reflected in a captured image based on the image values; extracting edge components from the noise; generating quantified characteristic values of the noise based on the edge components and the image values; and qualitatively and quantitatively evaluating the noise based on the characteristic values. BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a block diagram illustrating an image processing system in accordance with an embodiment of the present disclosure. FIG. 2 is a detailed block diagram illustrating an image sensor illustrated in FIG. 1 in accordance with an embodiment of the present disclosure. FIG. 3 is a schematic diagram illustrating a pixel array illustrated in FIG. 2 in accordance with an embodiment of the present disclosure. FIG. 4 is a detailed block diagram illustrating an image processor illustrated in FIG. 1 in accordance with an embodiment of the present disclosure. FIG. 5 is a detailed block diagram illustrating an analyzer illustrated in FIG. 4 in accordance with an embodiment of the present disclosure. FIG. 6 is a detailed block diagram illustrating a noise extractor illustrated in FIG. 5 in accordance with an embodiment of the present disclosure. FIG. 7 is a detailed block diagram illustrating an edge analyzer illustrated in FIG. 5 in accordance with an embodiment of the present disclosure. FIGS. 8 and 9 are schematic diagrams for describing an operation of the image processing system in accordance with an embodiment of the present disclosure. DETAILED DESCRIPTION Various embodiments of the present disclosure are described below with reference to the accompanying drawings, in order to describe in detail the present disclosure so that those with ordinary skill in art to which the present disclosure pertains may easily carry out the technical spirit of the present disclosure. It will be understood that when an element is referred to as being “connected to” or “coupled to” another element, the element may be directly connected to or coupled to the another element, or electrically connected to or coupled to the another element with one or more elements interposed therebetween. In addition, it will also be understood that the terms “comprises,” “comprising,” “includes,” and “including” when used in this specification do not preclude the presence of one or more other elements but may further include or have the one or more other elements, unless otherwise mentioned. In the description throughout the specification, some components are described in singular forms, but the present disclosure is not limited thereto, and it will be understood that the components may be formed in plural. FIG. 1 is a block diagram illustrating an image processing system 10 in accordance with an embodiment of the present disclo