The ultimate digital convergence platform: the camera phone
The volume of digital photos people are snapping today is dramatically reshaping the entire digital imaging ecosystem. Social networking Websites such as MySpace and YouTube have driven enormous increases in image uploading, while the availability of photo- and video-sharing sites like Flickr and iMovies have spurred similar amounts of image downloading. And today, uploading and downloading of photos and video occurs not just to and from PCs, but among a wide range of devices--PCs, laptops, PDAs and camera phones.

The camera phone is the most disruptive of these devices. Analyst firm Gartner notes that camera phones accounted for 48 percent of total worldwide mobile phones sales in 2006 and will jump to 81 percent by 2010.¹ Unit sales of camera phones will exceed one billion by 2010.²

Today, camera phone sales are surging as digital camera sales are stalling. Among the reasons: digital camera sales are reaching a saturation point with current technology. Multiple studies have shown that the average U.S. family of four already owns two or more digital cameras. On the other hand, improved camera phone technology, analyst firm Strategy Analytics notes, will result in camera phones capturing 15 percent of the low-end digital still camera market by 2010.³

Poor picture quality, limited camera phone memory and lack of an "ecosystem" to move pictures off of the phone and onto PCs or other storage devices might have made camera phones little more than a toy or a fad. However, a new wave of emerging technologies have encouraged early adopters to use their camera phones and have attracted a new set of users that would not have purchased a camera phone when their features were limited. As a result, just as digital still cameras (DSCs) dramatically shrank market demand for film cameras, new and improved camera phones are impacting sales of DSCs.

A recent survey by German optics firm Schneider Kreuznach polled 1,000 users in the U.S., Germany, China and India regarding their usage patterns. Highlights of their findings include:

• One out of four respondents indicated that in the future they would exclusively use their camera phones for picture-taking (early adopters), provided the quality matched that of today's upper mid-range digital cameras with approximately 6 million pixels.
• Under certain circumstances, 43 percent would be willing to replace their digital camera with a suitable camera phone. At present, only 32 percent would still prefer a digital camera.
• Users in India and China were particularly open-minded towards camera phone photography. In these countries, nearly eight out of ten of those questioned (79 percent) could imagine using only camera phones for picture-taking in future.
• While in India and China more than half of all respondents (60 and 52 percent respectively) already take pictures with their cell phones several times per week and in the USA more than a quarter (26 percent), Germany has the lowest number of so-called 'power users' (12 percent) and at the same time the highest number of non-users (59 percent).⁴

As the digital convergence trend continues, it becomes increasingly important for design engineers working to develop camera phones to have a strong understanding of what matters most when selecting an image sensor for a camera phone and stay informed of the latest image sensor technology developments that will enable camera phones to deliver higher quality images to consumers.

Choosing the Right Image Sensor
There are many criteria that can be used to choose an image sensor. Some of them are qualitative/subjective and some are quantitative/objective. When shopping for a CMOS image sensor for a camera phone, there are a few important "must know" quantitative metrics to keep in mind. They are:

• Pixel density--pixel density is a fundamental part of an image sensor's performance; the more pixels the sensor has, the more detailed the picture can be. But when selecting an image sensor, designers should not look at pixel count alone. As pixels decrease in size, they also decrease in performance. In order to add more pixels to sensors without compromising image quality, sensor vendors are working with a variety of new technologies to enhance pixel performance, and designers should be aware of what pixel technologies their vendors are using to boost performance as they shrink pixel size.
• Sensitivity--sensitivity measures the response of the sensor to light stimulus. It is often measured as mV/luxsec.
• Signal-to-noise ratio (SNR)--SNR is the logarithm of the ratio of a signal level to the standard deviation of the signal level. It measures the noise performance of the sensor. Noise as referred to here is a combination of readout noise, shot noise, dark current noise, fix pattern noise, temporal noise and others. The SNR is dependent on test conditions such as frame rate/integration time, luminance conditions and test target.
• Dynamic range--dynamic range measures the ability of an image sensor to adequately capture both bright and dark objects in the same images, and is often defined as the logarithm of the ratio of highest signal level to the lowest signal level (the noise floor level), with 54 db being the common specification for commercial image sensors. Image sensors with a wide dynamic range typically provide better performance in bright light environments (i.e. pictures taken in bright light environments appear "washed out" or blurry when taken with a sensor with poor dynamic range).
• Color representation--color reproduction is often quantified in terms of CIE Lab color space. The color space is a mathematical method to map human color vision in a three dimensional space where each color has a coordinate assigned to it. The color representation accuracy is determined by measuring the difference between the coordinates generated by the sensor and those generated by the human eye for the same color. The key metric used to measure color reproduction accuracy is "Delta E." Delta E is the spatial distance in the color space. A Delta E of below 10 would be a typical specification for most camera phone image sensors.
• White balance--white balance refers to a sensor's ability to accurately reproduce colors in changing light environments. Most camera systems have an auto white balance function, which can automatically change the white balance as lighting conditions change. Design engineers should look for image sensors equipped with a good auto white balance (AWB) control that provides right color reproduction.