360Photography

Texture acutance is a way of measuring the ability of a camera to capture images that preserve fine details, particularly the kind of low contrast detail (such as fine foliage, hair or fur) that can be blurred away by noise reduction or obliterated by excessive sharpening.

Sharpness is an important part of the quality of an image, but while it’s easy to look at an image and decide visually whether it’s sharp or not, the objective measurement of sharpness is less straightforward.

An image can be defined as ‘sharp’ if edges are sharp and if fine details are visible. In-camera processing means that it’s possible to have one of these (sharp edges) but not the other (fine details). Conventional MTF measurements tell us how sharp an edge is, but have drawbacks when it comes to measuring fine detail preservation. Image processing algorithms can detect edges and enhance their sharpness, but they can also find homogeneous areas and smooth them out to reduce noise.

Texture acutance, on the other hand, can qualify sharpness in terms of preservation of fine details, without being fooled by edge enhancement algorithms.

	A dead leaf pattern is designed to measure texture acutance. It’s obtained by drawing random shapes that occlude each other in the plane, like dead leaves falling from a tree. The statistics of this model follow the distribution statistics in natural images.
	In this example from a DSLR without edge enhancement, sharpness seems equal on edge and on texture. Many details are visible in the texture.
	In this second example, edges have been digitally enhanced, and the edge looks over sharp, with visible processing halos (‘ringing’). On the texture part, many details have disappeared.

At first sight, the images from these two cameras may appear equally sharp. A sharpness measurement on edges will indeed confirm this impression, and will even show that the second camera is sharper. But a closer examination of low contrasted textures shows that the first camera has better preservation of fine details than the second. The purpose of the texture acutance measurement is to qualify this difference.

Note: Acutance is a single value metric calculated from a MTF result. Acutance is used to assess the sharpness of an image as viewed by the human visual system, and is dependent on the viewing conditions (size of image, size of screen or print, viewing distance). Only the values of texture acutance are given here. The measurements are expressed as a percentage of the theoretical maximum for the chosen viewing condition. The higher the score, the more details can be seen in an image. 

For all DxOMark Mobile data presented on connect.dpreview.com we’re only showing 8MP equivalent values, which gives us a level playing field for comparison between smartphone cameras with different megapixel values by normalizing all to 8MP (suitable for fairly large prints). DxOMark also offers this data for lower resolution use-cases (web and onscreen). For more information on DxOMark’s testing methodology and acutance measurements please visit the website at www.dxomark.com.

Texture acutance is a touch higher under daylight than tungsten light.

In bright light the Moto G Plus is up with the best but drops off a little at lower light levels.

Visual Noise

DxOMark engineers don’t just point camera phones at charts, they also take and analyze plenty of real-world shots and score them accordingly. Their findings for the Lenovo Moto G Plus are:

Phone cameras, like entry-level compact cameras, tend to suffer from artifacts such as sharpening halos, color fringing, vignetting (shading) and distortion, which can have an impact on the visual appeal of the end result. DxOMark engineers measure and analyze a range of artifacts. Their findings after testing the Lenovo Moto G Plus are shown below:

• Cyan shift close to sky saturation visible in outdoor shots
• Some color fringing noticeable in backlit scenes
• Moiré is occasionally visible

Perceptual Scores

• Sharpness 4.5 out of 5
• Color fringing 3.6 out of 5

Measured findings

• Ringing center 7.6%
• Ringing corner 4.9%
• Max geometric distortion -0.4%
• Luminance shading 9.4%

Distortion and Chromatic Aberrations

The graph shows the magnification from center to edge (with the center normalized to 1). The Lenovo Moto G Plus shows a very slight pincushion distortion, which you are not going to notice in normal photography.

Chromatic aberrations are well under control.

Autofocus

DxOMark also tests autofocus accuracy and reliability by measuring how much the acutance – or sharpness – varies with each shot over a series of 30 exposures (defocusing then using the autofocus for each one). As with other tests these results are dependent on the viewing conditions (a little bit out of focus matters a lot less with a small web image than a full 8MP shot viewed at 100%). Using the 8MP equivalent setting, the Lenovo Moto G Plus performs very well in all light conditions. The overall score is 95/100 in bright light and 87/100 in low light.

Pros: 

• Accurate and repeatable autofocus in all conditions

Cons:

• Strong instabilities and overshoots in preview mode, particularly in low light
• Slow convergence, particularly in low light

Autofocus repeatability – average acutance difference with best focus: low light 3.26%, bright light 1.63%

Flash

The Lenovo Moto G Plus offers a dual-LED flash for illumination in very low light. DxOMark scored the camera a 77/100 overall for its flash performance. 

Pros: 

• Good exposure and vivid colors
• Pleasant colors when flash is mixed with tungsten light

Cons:

• Some focus and exposure irregularities
• Noticeable hue non-uniformity in the field
• Noise and attenuation visible in the corners

Overall DxOMark Mobile Score for Photo: 84 / 100

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Video Capture

DxOMark engineers put phone cameras through a similarly grueling set of video tests, and you can read their full findings on the DxOMark website here. Overall, DxOMark found the Lenovo Moto G Plus video mode to perform very well, with fast autofocus, good stabilization and good color. On the downside, some stepping can be visible when the AF is adjusting and luminance noise is visible in low light footage.

Pros: 

• Good stabilization
• Good color rendering and white balance
• Fast autofocus convergence
• Good noise reduction in outdoor conditions

Cons: 

• Some steps are visible during autofocus convergence in bright light
• Occasional autofocus inaccuracies in low light
• In low light some detail is lost and luminance noise is visible
• Visible steps in exposure adaptation

Overall DxOMark Mobile Score for Video: 81 / 100