Pixel Art Soft
Cameron Cortez
He proceeded to tell me it's high quality Gorilla whatever glass, and I responded that that's exactly why it should not scratch. If it's going to be this soft, I might as well buy the $100 Samsung phone.
I have a Pixel 6 and I noticed that the following soft-locks the device requiring a long press on power and volume up to shut down. Otherwise the device is completely unresponsive. I wonder if anyone else can confirm?
It appears that the software confuses the cropping of the screenshot and backing out of the crop screen. This leaves you on the crop screen, but with no interaction (perhaps it destroys the inputs but doesn't switch the screen?).
Principle of shape programmable magnetic pixel robot: (a) 3D magnetic vector programming system, (b) Structure of magnetic pixel film, (c) Mechanism of the Liquid-metal/NdFeB composites, (d) Magnetic encoding to the pixel robot, and (e) Magnetic response action.
Magnetic encoding and deformation prediction: (a) Initial/end shape and pixelation, (b) Rotation of magnetization vector, (d) Encoding planning process, (e) Initial and end shape of the six-pixel inchworm robot, and (f) Calculated vector angle when θBa= (90,90,0).
where θij= (θx,θy,θz)ij is the magnetic vector angle. By loading the codes of all pixels into the geometry matrix A, the magnetic encoding matrix M can be obtained.
Patterning performance of the magnetic pixel film: (a) Photograph of 2 2 mm2 magnetic pixel film, (b) Magnetic imaging of coding letters, (c) Photograph of 1 1 mm2 magnetic pixel film, (d) Magnetic imaging of QR code, (e) 6-pixel and 22-pixel structures, (f) Circular shape deformation.
Encoding schemes and response actions of the cross-shape pixel robot: (a) Photograph of the cross-shape robot, (b) Encoding scheme 1 and (c) Fan action, (d) Encoding scheme 2 and (e) Standing action, (f) Encoding scheme 3 and (g) Grasping action.
I've never had this problem before. I'm using the standard soft round brush to blend colors, which has always given a smooth effect, but now it suddenly looks all pixelated. The brush strokes also appears in rings instead of a smooth gradient. It looks as if the picture has been sharpened too much or saved in bad quality. I've already tried things like changing the brush settings, deleting photoshop preferences, increasing the RAM assigned to photoshop, but nothing works. Does anyone know what caused this? It's driving me insane! I get the same problem in an older version (Photoshop CS), so perhaps it's not photoshop itself?
Google released an OS update that causes pixel phone users (6, 7, 8, and Fold) that are using multiple profiles (a built in feature) to suddenly lose all access to either their main profile, or their entire phone altogether. Contacting support will only have them walk you through how to factory reset your device, and very rarely are they even acknowledging that this is a known bug.
WARNING: This bug behaves differently for different pixel models, this process worked for me to confirm the bug is still active without locking up my Pixel Fold. I do not guarantee that even on a pixel fold that this process will not cause data loss to your device, so proceed with caution.
Spatial quantization error arises in images that have been segmented using a hard threshold because each pixel in the segmented image can assume one of only two values, object (1) or background (0). When the number of possible pixel values in a segmented image increases, pixels in the segmented image can represent the object, the background, or the edge between the object and background.
Increasing the number of possible values for pixels in a segmented image is done by assigning pixel weights. A pixel weight is a number between 0 and 1.0 that indicates what the pixel represents. A pixel weight of 1.0 means the pixel is part of an object. A pixel weight of 0 means that the pixel is part of the background. A pixel weight between 0 and 1.0 means that the pixel is on the edge of an object.
When blob measures are computed using an image composed of weighted pixel values, measures such as area are computed by summing the pixel weights. When measures are computed based on pixel weights, the effects of spatial quantization error are greatly reduced. The figure below shows a simple 3x1 pixel blob. As the blob moves relative to the pixel grid, the total of the weights of the pixels that contain nonzero pixel values remains constant. This is the case even with the more complex shapes shown in Object position on a pixel grid affects reported area and Spatial quantization error increases with ratio of blob perimeter to blob area.
You convert a grey-scale image into an image segmented into weighted pixel values by supplying a soft binary threshold. Unlike a hard binary threshold, which consists of a single threshold value, a soft binary threshold consists of a range of threshold values. Pixels with values above the threshold range are assigned weights of 0 (background), pixels with values below the threshold range are assigned weights of 1 (object), and pixels with values within the threshold range are assigned weights between 0 and 1, typically in a linear manner. The figure below provides a graphical representation of a hard and soft binary threshold.
The European XFEL (EuXFEL) is an X-ray Free Electron Laser source, where up to 2700 extremely brilliant X-ray pulses of a single bunch train at \(4.5\,\textMHz\) are repeated every \(100\,\textms\)1. Its unique bunch scheme poses big design challenges for the imaging detector development. Three 1-megapixel detector types have been specifically designed with different concepts to cope with the required X-ray energy range, peak frame rate and dynamic range.
The Large Pixel Detector (LPD)2 has square pixels of \(500\)-μm size, and was designed to be operated in the energy range between \(5\) and \(20\,\textkeV\). Its pixel electronics features a charge sensitive amplifier (CSA) with three gain stages and a 512-cell analogue memory per stage operated in parallel. The digitization is executed during the train gaps thanks to an on-chip column-level analog-to-digital converter (ADC). The convenient gain path is selected off-chip in order to achieve the maximum dynamic range. The detector is part of the Femtosecond X-ray Experiments (FXE) scientific instrument at EuXFEL3.
The Depleted Field Effect Transistor (DEPFET) Sensor with Signal Compression (DSSC) is targeting the soft X-ray range between \(250\,\texteV\) and \(6\,\textkeV\). A first camera is based on passive miniaturized silicon drift detector (mini-SDD) cells of hexagonal shape with a side length of \(136\) μm7, corresponding to an equal-area diameter of \(247\) μm. The readout chain of each pixel comprises a CSA, a time-variant filter with trapezoidal weighting function, a 9-bit ADC with gain-and offset-trimming capability, and a SRAM with a storage capacity of 800 samples. Therewith, the DSSC detector not only offers the deepest storage capacity among the three detector versions, but is also unique with its per-pixel digitizer approach. Another unique feature concerns the power-down capability of unused analog and mixed-signal blocks during memory readout within inter-train gaps. In this way, the in-vacuum power dissipation is drastically reduced to \(149\,\textW\) in contrast to the AGIPD (\(550\,\textW\)). The power consumption of the 1-megapixel detector comprising the outside-vacuum electronics is \(263\,\textW\) compared to the AGIPD (\(1.2\,\textkW\)4) and LPD (\(12\,\textkW\)8). The gain of the signal processing chain can be adjusted in the CSA, in the filter and in the ADC, so that the current version of the DSSC imager with passive mini-SDD sensor covers the entire energy range with a gain granularity below one percent7. The imager reached an equivalent noise charge (ENC) of about \(60\,\text e^-\text rms\) at the peak frame rate of \(4.5\,\textMHz\), where the linear dynamic range is limited to maximal 9 bit. The camera was commissioned and is in use at the Spectroscopy and Coherent Scattering (SCS)9 and Small Quantum Systems (SQS) soft X-ray instruments at EuXFEL.
Other detectors targeting the soft X-ray regime well below \(1\,\textkeV\) are also based on the hybrid technology or originate from the class of charge-coupled devices (CCD) and monolithic CMOS imagers. They offer a higher spatial resolution but are limited in frame rates. To improve the performance at low X-ray energies, a novel CCD readout, called single electron sensitive readout (SiSeRO), is being developed at the MIT Lincoln Laboratory10. It features a floating gate amplifier composed by a MOSFET transistor with an internal gate used to read out the charge collected by the CCD matrix, and is based on the repetitive non-destructive readout (RNDR) DEPFET concept11. The authors of the paper could obtain a noise performance of \(15\,\text e^-\text rms\) at \(500\,\textkpixel/\rm s\), corresponding to a frame rate of about \(2\,\textHz\) of their readout concept. As hybrid candidate, the MÖNCH detector reached an ENC of about \(40\,\text e^-\text rms\) at \(3\,\text kfps\) for a unique \(25\)-μm pixel pitch12. The pnCCD detector with \(75\)-μm pixel pitch is part of the SQS instrument at EuXFEL and can be operated up to 100-Hz\(\textHz\) frame rates. In user experiments, an ENC around \(10\,\text e^-\text rms\) was achieved13. A monolithic example is the soft X-ray CMOS image sensor (sxCMOS), which is based on low-oxygen concentration Czochralski-grown silicon wafers and backside thinned to \(45\) μm. With a pixel pitch of \(22.4\) μm, the imager achieved \(8.1\,\text e^-\text rms\) noise level at a speed of \(450\,\textHz\)14. Except sxCMOS, all aforesaid cameras utilize thick high-resistivity wafer substrates for photon absorption, enabling their efficient use also at higher photon energies, whereas classical CMOS imagers make use of thin epitaxial layers. Recently, a sufficient quantum efficiency in soft X-ray domain was demonstrated for backside-illuminated imagers. Utilizing the \(10\) μm thick epi-layer of a commercial 180-nm CMOS technology and external post-processing of its backside, the \(27\)-μm pixel pitch Percival detector obtained a maximum frame rate and minimum ENC of about \(83\,\textHz\) and \(16\,\text e^-\text rms\), respectively15. Moreover, Desjardins et al.16, used a fully commercial CMOS imager (GSENSE 400BSI-GP) with \(4\)-μm epi-layer and \(11\)-μm pixel size for experiments at the soft X-ray branch of the metrologie beamline at SOLEIL synchrotron. They achieved a minimal ENC of \(6\,\text e^-\text rms\) at a frame rate of \(24\,\textHz\). Fully-depleted CMOS imager approaches based on thinned and post-processed high-resistivity substrates also exist for soft X-ray applications17,18. In order to comply with the targeted high sensitivity and frame rate, the pixel electronics of the \(50\)-μm pixel pitch ePixM detector is limited to nine transistors, and the digitization is shifted to a bump-bonded ADC tier. They strive for a frame rate and noise of \(24\,\textkHz\) and \(11\,\text e^-\text rms\), respectively.
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