Sony Patents a Location-Aware System for Cleaning Up Distorted Readings from Sensors
Sensors don't produce clean data everywhere at once, and Sony wants to fix the spots where distortion is most predictable by building a map of them before filtering even starts.
What Sony's location-based sensor filter actually does
Every time a camera or sensor captures a scene, it makes thousands of tiny errors. Some of those errors are random, but others happen in predictable spots, especially near the edges of what the sensor can "see" clearly. The result is visual noise or blurring that can fool software relying on that data.
Sony's patent describes a system that maps those trouble spots in advance. Instead of applying the same level of noise cleanup everywhere, it draws a filter map that marks the locations in a scene most likely to suffer from a specific kind of distortion called aliasing (think of the flickering, staircase-like edges you sometimes see in photos). The filter then works harder in those zones and eases off where the data is already clean.
The payoff is more accurate sensor output without over-processing the parts of the image that don't need it. That matters anywhere from camera systems to the kind of sensors that help cars or robots understand their surroundings.
defining a position of a sensing space in which aliasing is assumed in a filter map; and setting filter performance of a noise filter that performs filtering of sensing data for each position of the sensing space, based on the filter map.
Translation: The system maps out where sensor errors are likely to happen and adjusts the noise filters for each specific location.
How the filter map targets aliasing zone by zone
The patent describes a two-step process built around what it calls a filter map.
First, the system performs filter map generation: it identifies positions within a sensing space where aliasing is expected to occur. Aliasing is a sampling artifact (the digital equivalent of a vinyl record skipping) that appears when a sensor captures a signal that changes faster than the sensor can keep up with. In imaging, it shows up as jagged edges, moiré patterns, or false color. The key insight is that aliasing is not random across a scene; it tends to cluster in predictable zones based on geometry, angle, or the sensor's physical limits.
Second, the system performs filter processing: a noise filter reads the filter map and adjusts its strength position by position across the sensing space. Areas flagged as aliasing-prone get stronger filtering; areas without that flag get lighter treatment.
- Filter map generation encodes predicted distortion locations before filtering runs.
- The noise filter reads the map and applies variable strength across the sensing space.
- This avoids over-filtering clean regions, which can smear legitimate detail.
The claim is intentionally broad, covering any sensing data processed this way, not just optical cameras.
In the generation processing of the filter map, a position of a sensing space in which aliasing is assumed is defined in the filter map.
Translation: The software creates a map that highlights areas where sensor distortion is expected to occur.
What this means for cameras, lidar, and imaging quality
For anyone using a product with a camera or depth sensor, over-aggressive noise filtering is already a known problem: it erases fine texture and detail in the name of a "clean" image. Under-filtering leaves visual artifacts that confuse both the human eye and any AI software reading the feed. Sony's approach tries to thread that needle by being selective rather than uniform.
Sony's interest in sensor-level image processing shows up across a wide range of its product lines, from mirrorless cameras to PlayStation peripherals to automotive sensors. A location-aware filter map could, in principle, improve output quality in any of those contexts without demanding more powerful hardware, just more precise software.
Sony's 16th filing in our sensor patent coverage since June follows earlier applications like one checking surroundings before transmitting and one reading body electrical signals that we've tracked.
Sony's sensors sit inside cameras, phones, and cars, and this fix targets the specific zones in a sensor's field of view where distortion predictably creeps in, applying heavier cleanup exactly there rather than treating every part of the image the same way.
For a photographer, edges stay sharp in tricky light instead of going soft. For someone in a car with driver-assistance features, the system is less likely to misread an object at the periphery of what the sensors can see, which is exactly where mistakes matter most.
The technology asks nothing of the user. They simply encounter fewer of those moments where an image looks slightly wrong or a safety feature hesitates, and that quiet reliability, spread across millions of devices, is the whole point.
There are more where this came from
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The drawings
12 drawing sheets from US 2026/0301360 A1 · click any drawing to enlarge
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