Planet Arduino

Working with graphics on microcontrollers has always meant focusing on making the most of limited resources. Particularly in the 8-bit era, all manner of tricks were used to get low-performance chips to achieve feats beyond their lowly station. However, these days, we’re blessed with 32-bit workhorses with clock speeds in the tens, or even hundreds, of MHz and many kilobytes of RAM to match. It’s these higher performance chips [Larry] had in mind when writing his JPEGDEC library.

As [Larry] discusses in a blog post on the topic, JPEG libraries already exist for the Arduino platform. However, many of these are aimed at 8-bit platforms with tiny amounts of RAM. While it’s possible to decode JPEGs piece by piece with some intelligent code under these conditions, it’s possible to go much faster when you’ve got a little more headroom. [Larry] does a great job of explaining the variety of optimizations he’s developed in the two decades since writing his first JPEG decoder back in 1994. From eliminating unnecessary marker checks to ignoring unneeded data for scaled-down output, it all adds up to get the job done faster. The library targets the Cortex-M0+, or any chip with a minimum of 20K of RAM, as its bare minimum to operate. Faster chips with higher clock rates naturally do better, and [Larry] provides benchmark decoding times for various common hardware using the library.

We’ve featured [Larry]’s GIF decoder for the Arduino platform before, again a useful library that’s optimised for good performance. If you’ve got your own neat tricks for image processing on microcontrollers, you know how to call!

When you think of image processing, you probably don’t think of the Arduino. [Jan Gromes] did, though. Using a camera and an Arduino Mega, [Jan] was able to decode input from an Arduino-connected camera into raw image data. We aren’t sure about [Jan’s] use case, but we can think of lots of reasons you might want to know what is hiding inside a compressed JPEG from the camera.

The Mega is key, because–as you might expect–you need plenty of memory to deal with photos. There is also an SD card for auxiliary storage. The camera code is straightforward and saves the image to the SD card. The interesting part is the decoding.

The use case mentioned in the post is sending image data across a potentially lossy communication channel. Because JPEG is compressed in a lossy way, losing some part of a JPEG will likely render it useless. But sending raw image data means that lost or wrong data will just cause visual artifacts (think snow on an old TV screen) and your brain is pretty good at interpreting lossy images like that.

Just to test that theory, we took one of [Joe Kim’s] illustrations, saved it as a JPEG and corrupted just a few bytes in a single spot in it. You can see the before (left) and after (right) picture below. You can make it out, but the effect of just a few bytes in one spot is far-reaching, as you can see.

The code uses a library that returns 16-bit RGB images. The library was meant for displaying images on a screen, but then again it doesn’t really know what you are doing with the results. It isn’t hard to imagine using the data to detect a specific color, find edges in the image, detect motion, and other simple tasks.

Sending the uncompressed image data might be good for error resilience, but it isn’t good for impatient people. At 115,200 baud, [Jan] says it takes about a minute to move a raw picture from the Arduino to a PC.

We’ve seen the Arduino handle a single pixel at a time. Even in color. The Arduino might not be your first choice for an image processing platform, but clearly, you can do some things with it.

This camera module can perform image processing such as AWB (auto white balance), AE (automatic exposure) and AGC (automatic gain control), for the video signal coming from CMOS sensor. What’s more, in fusion of other advanced technology such as image enhancement processing under low illumination, and image noise intelligent forecast and suppress, this module would output high quality digital video signals by standard CCIR656 interface. OV7670 built-in JPEG decoder supported reatime encoding for collected image, and external controller can easily read the M – JPEG video streams, achieving the camera design of double stream. OV7670 supported motion detection and OSD display function of screen characters and pattern overlay, capable of self-defining detection area and sensitivity.

OV7670 Camera Module DIY Guide - [Link]