Circular image compression

Abstract

In one implementation, a method of compressing an image is performed at a device that includes one or more processors and a non-transitory memory. The method includes obtaining an uncompressed image. The method includes compressing the uncompressed image by mapping a substantially circular portion of the uncompressed image to a substantially square portion of a compressed image to generate the compressed image, wherein a central region of the substantially circular portion of the uncompressed image is compressed more than remaining portions of the substantially circular portion of the uncompressed image.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. Provisional Patent Application No. 63 / 403,943, filed on September 6, 2022, which is hereby incorporated by reference in its entirety. Technical Field

[0003] The present disclosure generally relates to systems, methods, and devices for compressing images. Background Art

[0004] Image compression reduces the cost of storage and / or transmission of digital images. BRIEF DESCRIPTION OF THE DRAWINGS

[0005] In order that the present disclosure may be understood by those skilled in the art, a more particular description will be given with reference to some exemplary implementations, some of which are illustrated in the accompanying drawings.

[0006] Figure 1 An uncompressed image is shown according to some implementations.

[0007] FIG. 2A to FIG. 2D According to some specific implementations Figure 1 Various compressed versions of an uncompressed image.

[0008] FIG. 3A to FIG. 3C According to some specific implementations Figure 1 and FIG. 2A to FIG. 2D Various charts of various image resolutions.

[0009] Figure 4 A graph showing a non-uniform stretch function according to some implementations.

[0010] Figure 5 A flowchart representation of a method of compressing an image according to some specific implementations is shown.

[0011] Figure 6 A rectangular uncompressed image is shown according to some implementations.

[0012] Figure 7 A rectangular compressed image is shown according to some implementations.

[0013] As is common practice, the various features illustrated in the drawings may not be drawn to scale. Therefore, the sizes of the various features may be arbitrarily expanded or reduced for clarity. In addition, some of the drawings may not depict all of the components of a given system, method, or device. Finally, throughout the specification and drawings, similar reference numerals may be used to represent similar features. Summary of the invention

[0014] Various embodiments disclosed herein include devices, systems, and methods for compressing images. In various embodiments, the method is performed by a device including one or more processors and a non-transitory memory. The method includes obtaining an uncompressed image. The method includes compressing the uncompressed image to generate the compressed image by mapping a substantially circular portion of the uncompressed image to a substantially square portion of a compressed image, wherein a central area of ​​the substantially circular portion of the uncompressed image is compressed more than a remaining portion of the substantially circular portion of the uncompressed image.

[0015] According to some specific implementations, a device includes one or more processors, non-volatile memory, and one or more programs; one or more programs are stored in the non-volatile memory and are configured to be executed by one or more processors. One or more programs include instructions for executing or causing the execution of any of the methods described herein. According to some specific implementations, a non-volatile computer-readable storage medium stores instructions that, when executed by one or more processors of the device, cause the device to execute or cause the execution of any of the methods described herein. According to some specific implementations, a device includes: one or more processors, non-volatile memory, and a component for executing or causing the execution of any of the methods described herein. DETAILED DESCRIPTION

[0016] In various embodiments, an image captured using an image sensor with a fisheye lens includes information only in a substantially circular region of the image. Such an image may be referred to as a circular image. In addition, in various embodiments, the radial resolution of a circular image decreases as the distance from the center of the image increases. Image compression may reduce the cost of storage and / or transmission of such images. In various embodiments, image compression may be lossless or lossy. Lossy image compression aims to significantly reduce the size of an image while minimizing the loss of visual fidelity. To this end, in various embodiments, a substantially circular portion of an uncompressed image is mapped to a substantially square portion of an uncompressed image so that more pixels of the compressed image encode information. In addition, a central region with a high radial resolution is compressed more (e.g., more downsampled) than other regions with a lower radial resolution. Reducing the resolution of a central region with a high radial resolution introduces less visual differences than reducing the resolution of other regions with a lower resolution.

[0017] Figure 1An uncompressed image 100 according to some implementations is shown. The uncompressed image 100 includes a rectangular matrix of pixels with corresponding pixel values. In various implementations, the uncompressed image 100 is captured in a physical environment using an image sensor with a fisheye lens. Therefore, the uncompressed image 100 represents a large field of view of the physical environment. In various implementations, the fisheye lens focuses light from the physical environment onto a substantially circular area of ​​the image sensor. Therefore, although the uncompressed image 100 includes a rectangular matrix of pixels, only the pixel values ​​of the pixels in the substantially circular area 101 of the uncompressed image 100 represent the physical environment. The pixel values ​​of the pixels outside the substantially circular area 101 (shown in black) do not encode information and may represent noise or be set to zero.

[0018] In various implementations, to compress the uncompressed image 100, the image 100 is uniformly downsampled. Figure 2A A uniformly downsampled compressed image 210 (a uniformly downsampled version of image 100) is shown. Uniformly downsampled compressed image 210 includes a rectangular matrix of pixels having pixel values. In uniformly downsampled compressed image 210, substantially circular region 101 of uncompressed image 100 is represented by a similar (but smaller) substantially circular region 211. In addition, uniformly downsampled compressed image 210 includes pixels outside of substantially circular region 211 having pixel values ​​that do not encode information.

[0019] In various implementations, in order to compress the uncompressed image 100 and reduce the number of pixels having pixel values ​​that do not encode information, a substantially circular region 101 of the uncompressed image 100 is mapped to a substantially square region of the compressed image using a circle-to-square mapping. Various circle-to-square mappings may be used, including radial stretching, Shirley-Chiu mapping, Fernandez-Guasti's squarish mapping, elliptical arc mapping, or conformal mapping.

[0020] Assuming the image is M×N, the normalized coordinates of the pixel at point (m,n) in the image are (2m / M–1,–2n / N–1). Therefore, the image goes from -1 to 1 both horizontally and vertically. In addition, the radius of a pixel is the distance from the center of the image to the pixel location in the normalized coordinate system, or The normalized radius of a pixel in the uncompressed image 100 is the radius of the pixel divided by the length of a line segment passing through the pixel from the center to the edge of the substantially circular region 101. If the substantially circular region 101 is a perfect circle, the length of the line segment is always 1 and the normalized radius is equal to the radius. However, in various implementations, the substantially circular region is truncated (e.g., in the embodiments described below). Figure 6), and the normalized radius is not equal to the radius. The normalized radius of a pixel in the circular-to-square compressed image 100 is the radius of the pixel divided by the length of a line segment passing through the pixel from the center of the substantially square region to its edge. The length of the segment varies as the angle changes. For example, the length is 1 at 0 degrees and √2 at 45 degrees. In various implementations, the substantially square region has rounded corners (e.g., as described below). Figure 7 (middle), and the normalized radius is less than √2 at 45 degrees.

[0021] To map a circle to a square using a uniform radial stretch, the radius of each point in the circle is stretched (or scaled) in proportion to the distance from the center of the square to its edge at that angle, based on the angle of the circle. Thus, the normalized radius of a point in the compressed image is the same as the normalized radius of a point in the uncompressed image 100.

[0022] For example, where u and v are normalized coordinates for a circle, x and y are normalized coordinates for a square, and

[0023]

[0024] Figure 2B A uniformly stretched square compressed image 220 is shown formed by mapping a substantially circular region 101 of an uncompressed image to a square using a uniform radial stretch. Thus, a point A in the uncompressed image 100 having a radius of 0 is represented by a point A in the uniformly stretched square compressed image 220 having a radius of 0. A point B in the uncompressed image 100 having a radius of approximately 0.5 and an angle of 0 degrees is represented by a point B in the uniformly stretched square compressed image 220 having a radius of approximately 0.5 and an angle of 0 degrees. A point C in the uncompressed image 100 having a radius of approximately 1 and an angle of 0 degrees is represented by a point C in the uniformly stretched square compressed image 220 having a radius of approximately 1 and an angle of 0 degrees. A point D in the uncompressed image 100 having a radius of approximately 1 and an angle of 90 degrees is represented by a point D in the uniformly stretched square compressed image 220 having a radius of approximately 1 and an angle of 90 degrees. Point E in the uncompressed image 100 with a radius of approximately 1 and an angle of 45 degrees is represented by point E in the uniformly stretched square compressed image 220 with a radius of approximately √2 and an angle of 45 degrees (compared to a radius of approximately 1 in the uniformly downsampled compressed image 210).

[0025] In various implementations, the radial resolution of an image captured using an image sensor with a fisheye lens is highest at the center of the image and decreases with increasing distance from the center. Figure 3AA graph 300 shows the radial resolution of the uncompressed image 100 as a function of eccentricity (degrees from the center). The radial resolution is approximately 50 PPD (pixels per degree) at the center of the uncompressed image 100, decreases to approximately 40 PPD at approximately 50 degrees eccentricity, and further decreases to approximately 20 PPD at approximately 90 degrees eccentricity.

[0026] Thus, the center of the uncompressed image 100 encodes much more information than the outer regions. Compressing the uncompressed image 100 using uniform radial stretching uniformly reduces the radial resolution. Figure 3B A graph 320 shows the radial resolution of the uniformly stretched square compressed image 220 as a function of eccentricity. The radial resolution is approximately 45 PPD (pixels per degree) at the center of the uniformly stretched square compressed image 220, decreases to approximately 35 PPD at approximately 50 degrees eccentricity, and further decreases to approximately 15 PPD at approximately 90 degrees eccentricity.

[0027] Thus, information at the outer regions of the uncompressed image 100 (which is already insufficient compared to the center) is discarded in the uniformly stretched square compressed image. Furthermore, in various implementations, the display may be limited with respect to the radial resolution that can be displayed. For example, in various implementations, the display may display up to 40 PPD. Thus, information at the center of the uniformly stretched square compressed image 220, which has a PPD greater than 45 PPD, is not displayable.

[0028] Therefore, in various implementations, a non-uniform circular-to-square mapping is used, wherein a central region 102 of the substantially circular region 101 is compressed more than an outer region 103 that includes the remainder of the substantially circular region 101 .

[0029] For example, where u and v are the normalized coordinates of a circle, and x and y are the normalized coordinates of a square, and f(r) is a non-uniform stretching function,

[0030]

[0031] In various implementations, the non-uniform stretching function is a convex function. Figure 4 A graph 400 of an example non-uniform stretch function is shown. The non-uniform stretch function is linear between an input value of 0 and a first value (r1), and outputs values ​​from 0 to a second value (r2) less than the first value. The non-uniform stretch function is linear between an input value of the first value and 1, and outputs values ​​from the second value to 1. In various implementations, different non-uniform stretch functions are used for the horizontal component and the vertical component.

[0032] Figure 2CA non-uniformly stretched square compressed image 230 is shown formed by mapping a substantially circular region 101 of an uncompressed image to a square using a non-uniform radial stretch. Thus, a point A in the uncompressed image 100 having a radius of 0 is represented by a point A in the non-uniformly stretched square compressed image 230 having a radius of 0. A point B in the uncompressed image 100 having a radius of about 0.5 and an angle of 0 degrees is represented by a point B in the non-uniformly stretched square compressed image 230 having a radius of about 0.25 and an angle of 0 degrees (compared to a radius of about 0.5 in the uniformly stretched square compressed image 220). A point C in the uncompressed image 100 having a radius of about 1 and an angle of 0 degrees is represented by a point C in the non-uniformly stretched square compressed image 230 having a radius of about 1 and an angle of 0 degrees. A point D in the uncompressed image 100 having a radius of about 1 and an angle of 90 degrees is represented by a point D in the non-uniformly stretched square compressed image 230 having a radius of about 1 and an angle of 90 degrees. Point E in the uncompressed image 100 with a radius of approximately 1 and an angle of 45 degrees is represented by point E in the non-uniformly stretched square compressed image 230 with a radius of approximately √2 and an angle of 45 degrees.

[0033] By non-uniform stretching, the radial resolution of the central region can be limited (eg, to a maximum display resolution) while maintaining the radial resolution of the outer region. Figure 3C A graph 330 is shown showing the radial resolution of the non-uniform stretched square compressed image 230 as a function of eccentricity. The radial resolution is about 40 PPD (pixels per degree) from the center of the non-uniform stretched square compressed image 230 to about 50 degrees eccentricity, then decreases to about 20 PPD at about 90 degrees eccentricity.

[0034] Due to radial stretching, there are more pixels (and information) along the diagonals than along the equator and meridians in the non-uniformly stretched square compressed image 230. Therefore, in various implementations, the substantially circular region 101 of the uncompressed image is rotated or rotated by -45 degrees (or 45 degrees, 135 degrees, or -135 degrees) before the mapping is applied to keep as much information along the equator and meridians of the uncompressed image 100. In various implementations, the rotation is integrated into the mapping to form a rotated non-uniform circular-to-square mapping. Figure 2D A rotated non-uniformly stretched square compressed image 240 is shown.

[0035] Thus, point A in the uncompressed image 100 with a radius of 0 is represented by point A in the rotated non-uniformly stretched square compressed image 240 with a radius of 0. Point B in the uncompressed image 100 with a radius of about 0.5 and an angle of 0 degrees is represented by point B in the rotated non-uniformly stretched square compressed image 240 with a radius of about (√2) / 4 and an angle of -45 degrees. Point C in the uncompressed image 100 with a radius of about 1 and an angle of 0 degrees is represented by point C in the rotated non-uniformly stretched square compressed image 240 with a radius of about √2 and an angle of -45 degrees. Point D in the uncompressed image 100 with a radius of about 1 and an angle of 90 degrees is represented by point D in the rotated non-uniformly stretched square compressed image 240 with a radius of about √2 and an angle of 45 degrees. Point E in the uncompressed image 100 with a radius of about 1 and an angle of 45 degrees is represented by point E in the rotated non-uniformly stretched square compressed image 240 with a radius of about 1 and an angle of 0 degrees.

[0036] In various embodiments, a compressed image is provided to a player, which decompresses the compressed image and displays the decompressed image. In various embodiments, in addition to the compressed image, the player is also provided with a decompression map used by the player to decompress the compressed image. In various embodiments, the decompression production is provided to the player as a set of vertices and corresponding pixel positions on a unit sphere to form a triangular mesh. Therefore, in various embodiments, the decompression map is a piecewise affine map because an affine map is defined by three point pairs. Therefore, in various embodiments, the compression map is also a piecewise affine map.

[0037] The above-mentioned circle-to-square mapping is neither affine nor piecewise affine. Therefore, in various specific implementations, a piecewise affine mapping is defined, wherein each of the multiple vertices in the uncompressed image 100 is mapped to a corresponding vertex in the compressed image using one of the above-mentioned circle-to-square mappings. In various specific implementations, the vertices in the uncompressed image 100 are a substantially regular polygonal mesh, such as a polyhedron that approximates a sphere. In addition, an affine mapping defined by three vertices is used to map the pixels of the uncompressed image 100 within the triangle defined by the three vertices to corresponding pixel locations in the compressed image. The corresponding vertices in the compressed image are provided to the player as part of the decompression map.

[0038] Figure 55 is a flowchart representation of a method 500 for compressing an image according to some implementations. In various implementations, the method 500 is performed by a device including one or more processors and non-transitory memory. In some implementations, the method 500 is performed by a processing logic component (including hardware, firmware, software, or a combination thereof). In some implementations, the method 500 is performed by a processor executing instructions (e.g., code) stored in a non-transitory computer-readable medium (e.g., memory).

[0039] In block 510, method 500 begins, where a device obtains an uncompressed image. In various implementations, obtaining the uncompressed image includes capturing an image of the physical environment using an image sensor having a fisheye lens. In various implementations, the uncompressed image is a rectangular matrix of pixels having corresponding pixel values. In various implementations, the uncompressed image includes a substantially circular portion that includes pixels having pixel values ​​that encode information, and a remaining portion of the pixels have pixel values ​​that do not encode information. Although Figure 1 The uncompressed image 100 is shown as a square, but in various implementations, the uncompressed image is a rectangle having a first size that is different from a second size. Figure 1 The substantially circular portion 101 is shown as a complete circle, but in various implementations, the uncompressed image includes a substantially circular portion that is not a perfect circle, such as a substantially circular portion with top and bottom portions clipped. Figure 6 A rectangular uncompressed image 600 is shown including a substantially circular region 601 that is not a perfect circle.

[0040] In block 520, method 500 continues with the device compressing the uncompressed image to generate a compressed image by mapping a substantially circular portion of the uncompressed image to a substantially square portion of the compressed image. The compressed image is a matrix of pixels having corresponding pixel values. In various implementations, the compressed image is a square matrix of pixels. In various implementations, the compressed image includes fewer pixels than the uncompressed image. Although FIG. 2B to FIG. 2D The substantially circular region 101 is shown as a complete square region into which it is mapped, but in various implementations, the compressed image includes substantially square portions that are not perfect squares, such as being rectangular having a first size different from a second size or having rounded corners. Figure 7 A rectangular compressed image 700 is shown including a substantially square region 701 that is not a perfect square.

[0041] In various implementations, a central area of ​​the substantially circular portion of the uncompressed image is compressed more than the remainder of the substantially circular portion of the uncompressed image. Figure 2C and Figure 2D , a central region 102 of the substantially circular portion 101 of the uncompressed image 100 is more compressed than an outer region 103 in the non-uniformly stretched square compressed image 230 and the rotated non-uniformly stretched square compressed image 240 .

[0042] In various implementations, mapping the substantially circular portion of the uncompressed image to the substantially square portion of the compressed image includes a non-uniform radial stretch. Thus, in various implementations, a normalized radius of a particular pixel in a central region of the uncompressed image is larger than a normalized radius of a corresponding pixel in the compressed image. Similarly, in various implementations, a normalized radius of a particular pixel in a remaining portion of the substantially circular portion of the image is smaller than a normalized radius of a corresponding pixel in the compressed image.

[0043] In various implementations, the radial resolution of the uncompressed image decreases as a function of increasing eccentricity. Thus, in various implementations, the radial resolution of the uncompressed image decreases from a maximum value at the center of the uncompressed image as the normalized radius increases. In various implementations, each point in the compressed image has a radial resolution that is less than a maximum radial resolution of the uncompressed image. In various implementations, the maximum radial resolution of the compressed image is less than or equal to a display threshold, such as a maximum radial resolution that can be displayed by a particular display. In various implementations, the radial resolution of the compressed image is substantially constant in a central region of the compressed image corresponding to a central region of a substantially circular portion of the uncompressed image.

[0044] In various implementations, the horizontal radial resolution of the compressed image is different from the vertical radial resolution of the compressed image. For example, in various implementations, the vertical radial resolution (in the central region of the compressed image) is about 38 PPD, and the horizontal radial resolution (in the central region of the compressed image) is about 36 PPD.

[0045] In various implementations, mapping the substantially circular portion of the uncompressed image to the substantially square portion of the compressed image includes mapping a plurality of vertices of the uncompressed image to corresponding vertices of the compressed image. Further, in various implementations, pixels of the uncompressed image within a triangle defined by the three vertices are mapped to corresponding pixel locations in the compressed image using an affine mapping defined by the three vertices. Thus, in various implementations, mapping the substantially circular portion of the uncompressed image to the substantially square portion of the compressed image includes performing piecewise affine mapping.

[0046] In various implementations, mapping the substantially circular portion of the uncompressed image to the substantially square portion of the compressed image includes additional mapping. For example, in various implementations, the uncompressed image is rotated prior to compression to increase sampling along the equator and prime meridian. In various implementations, the rotation is incorporated into the mapping. Thus, in various implementations, the substantially circular portion of the uncompressed image is rotated by approximately 45 degrees, 135 degrees, 225 degrees, or 315 degrees in the compressed image.

[0047] In various implementations, mapping includes image correction (e.g., stereo image correction). In various implementations, the camera includes two or more image sensors that generate a set of two or more images. The images may be vertically offset due to camera misalignment, lens distortion, or other factors. Image correction projects the images onto a common image plane in a manner such that corresponding points in the images have the same row coordinates. Image correction is a projection (or mapping) that corrects the images to appear as if two or more image sensors are parallel. It may be particularly beneficial to perform image correction before compression to improve the efficiency of the encoding stage with encoding that uses inter-frame similarity (e.g., block matching, motion vector prediction, bundling, etc.).

[0048] In various implementations, the mapping includes lens distortion correction, perspective correction, or any other projection or mapping.

[0049] Although various aspects of specific implementations within the scope of the appended claims are described above, it should be apparent that the various features of the above-mentioned specific implementations can be embodied in a variety of forms, and any specific structures and / or functions described above are merely illustrative. Based on this disclosure, it should be understood by those skilled in the art that the aspects described herein can be implemented independently of any other aspects, and two or more of these aspects can be combined in various ways. For example, a device and / or a method can be implemented using any number of aspects set forth herein. In addition, in addition to or different from one or more aspects set forth herein, such a device and / or such a method can be implemented using other structures and / or functions.

[0050] It will also be understood that, although the terms "first", "second", etc. may be used to describe various elements in this article, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, a first node may be referred to as a second node, and similarly, a second node may be referred to as a first node, which changes the meaning of the description, as long as all occurrences of the "first node" are consistently renamed and all occurrences of the "second node" are consistently renamed. Both the first node and the second node are nodes, but they are not the same node.

[0051] The terms used herein are only for describing specific implementations and are not intended to limit the claims. As used in the description of this specific implementation and the appended claims, the singular forms of "one", "a kind of" and "the" are intended to also cover the plural forms, unless the context clearly indicates otherwise. It will also be understood that the term "and / or" used herein refers to and covers any and all possible combinations of one or more items in the associated listed items. It will also be understood that the term "comprising" when used in this specification specifies the presence of stated features, integers, steps, operations, elements and / or parts, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, parts, and / or their groupings.

[0052] As used herein, the term "if" may be interpreted to mean "when the antecedent is true" or "when the antecedent is true" or "in response to determining" or "upon determining" or "in response to detecting" that the antecedent is true, depending on the context. Similarly, the phrase "if it is determined that [the antecedent is true]" or "if [the antecedent is true]" or "when [the antecedent is true]" is interpreted to mean "upon determining that the antecedent is true" or "in response to determining" or "upon determining" that the antecedent is true or "when detecting that the antecedent is true" or "in response to detecting" that the antecedent is true, depending on the context.

Claims

1. A method, comprising: At a device having one or more processors and non-transitory memory; Get uncompressed image; as well as The uncompressed image is compressed by mapping a substantially circular portion of the uncompressed image to a substantially square portion of the compressed image to generate the compressed image, wherein a central area of ​​the substantially circular portion of the uncompressed image is more compressed than a remaining portion of the substantially circular portion of the uncompressed image. 2 . The method of claim 1 , wherein obtaining the uncompressed image comprises capturing an image of a physical environment using an image sensor having a fisheye lens.

3. The method of claim 1 or 2, wherein in the compressed image, the substantially circular portion of the uncompressed image is rotated by approximately 45 degrees, 135 degrees, 225 degrees or 315 degrees.

4. The method of any one of claims 1 to 3, wherein mapping the substantially circular portion of the uncompressed image to the substantially square portion of the compressed image comprises a non-uniform radial stretch.

5. The method according to any one of claims 1 to 4, wherein a normalized radius of a specific pixel in the central area of ​​the uncompressed image is larger than a normalized radius of a corresponding pixel in the compressed image.

6. A method according to any one of claims 1 to 5, wherein the normalized radius of a particular pixel in the remaining portion of the substantially circular portion of the image is smaller than the normalized radius of a corresponding pixel in the compressed image.

7. The method according to any one of claims 1 to 6, wherein a maximum radial resolution of the compressed image is less than or equal to a display threshold.

8. The method of any one of claims 1 to 7, wherein mapping the substantially circular portion of the uncompressed image to a substantially square portion of the compressed image comprises: Mapping a plurality of vertices of the uncompressed image to corresponding vertices of the compressed image; as well as Pixels of the uncompressed image within a triangle defined by the three vertices are mapped to corresponding pixel locations in the compressed image using an affine mapping defined by the three vertices.

9. The method of any one of claims 1 to 8, wherein mapping the substantially circular portion of the uncompressed image to the substantially square portion of the compressed image comprises performing a piecewise affine mapping.

10. The method of any one of claims 1 to 9, wherein mapping the substantially circular portion of the uncompressed image to the substantially square portion of the compressed image comprises performing stereo rectification.

11. The method according to any one of claims 1 to 10, wherein the compressed image comprises fewer pixels than the uncompressed image.

12. A device, comprising: one or more processors; non-transitory memory; and One or more programs stored in the non-transitory memory, which, when executed by the one or more processors, cause the device to perform any of the methods according to claims 1 to 11.

13. A non-transitory memory storing one or more programs which, when executed by one or more processors of a device, cause the device to perform any of the methods of claims 1 to 11.

14. A device, comprising: one or more processors; non-transitory memory; and Means for causing the apparatus to perform any of the methods according to claims 1 to 11.

15. A device, comprising: non-transitory memory; and One or more processors, the one or more processors configured to: Get uncompressed image; as well as The uncompressed image is compressed by mapping a substantially circular portion of the uncompressed image to a substantially square portion of the compressed image to generate the compressed image, wherein a central area of ​​the substantially circular portion of the uncompressed image is more compressed than a remaining portion of the substantially circular portion of the uncompressed image.

Images