📝 Lossy compression techniques in multimedia (31 MCQs)

📖 Explanation: Lossy compression intentionally removes information that is less perceptible to humans, resulting in a smaller file. This discarded data cannot be perfectly recovered, which distinguishes it from lossless methods. The trade‑off is between reduced size and a potential loss in fidelity, making option B the correct description.

📖 Explanation: Lossy audio streaming typically relies on MP3 because it provides a good balance between compression efficiency and audio quality. FLAC and ALAC are lossless, preserving all samples, while WAV is uncompressed. Therefore MP3, a widely supported lossy format, is the appropriate answer.

📖 Explanation: The QP determines how aggressively transform coefficients are quantized; larger QP values produce coarser quantization, yielding higher compression at the expense of visual quality. It does not affect frame timing, color precision, or network characteristics, making option C the correct choice.

📖 Explanation: Halving the bitrate forces the encoder to increase compression, typically removing more detail or raising the quantization level. Viewers usually notice a modest decline in sharpness or color fidelity, but the video remains watchable, so a slight degradation is the expected outcome.

📖 Explanation: A lower compression ratio (2:1) means the compressed file is larger, so more bits must be transmitted per unit time. Therefore Codec Y, with the smaller reduction, will typically need more bandwidth than Codec X.

📖 Explanation: Lossy codecs are designed to discard perceptually insignificant information, so the remaining data already tolerates minor corruption. When packets are lost, the visual or auditory impact is often less noticeable compared with lossless data, which contains every original detail and thus shows more obvious artifacts.

📖 Explanation: Lossy codecs typically produce smaller packets and can tolerate occasional loss, allowing the receiver to use a modest buffer to smooth jitter without needing the larger buffers required for lossless streams that must preserve every bit.

📖 Explanation: Because H.264 already discards redundant detail, minor missing frames are less noticeable; the decoder can use predictive techniques to fill gaps. A lossless codec would retain every detail, making any missing frame stand out sharply, so H.264’s lossy approach provides smoother continuity.

📖 Explanation: Doubling the compression ratio reduces the amount of data sent per packet by half, directly cutting the required bandwidth while leaving timing parameters unchanged. Latency, loss, and jitter are not directly altered by the compression ratio itself.

📖 Explanation: Lossy compression removes redundant and less important information, which often reduces predictability and raises the measured entropy of the remaining data because the distribution becomes less uniform. Hence the stored data’s entropy tends to increase after aggressive lossy reduction.

📖 Explanation: High loss suggests the network cannot sustain the current data rate. Reducing the frame rate lowers the amount of data transmitted per second, allowing the existing bitrate to be maintained with fewer frames, which is a common response when using lossy codecs.

📖 Explanation: Live streaming benefits from reduced bandwidth, which lossy compression provides by discarding perceptually irrelevant information. Lossless methods preserve every detail but demand higher transmission rates and often higher processing overhead, making option B the most accurate comparison.

📖 Explanation: Increasing QP coarsens quantization, so more coefficients are rounded to zero, raising the compression ratio. Simultaneously, the loss of detail introduces visible artifacts such as blocking or blurring, so both ratio and artifacts grow together.

📖 Explanation: RTP is responsible for the real‑time transport of media packets, while RTCP periodically sends control packets containing statistics (e.g., loss, jitter) that enable the sender to adjust lossy encoding parameters. This separation of data and control is essential for adaptive compression.

📖 Explanation: SIP’s extensible architecture allows the inclusion of many codec identifiers in its SDP payload, making it straightforward to negotiate lossy codecs. Although both protocols can carry codec information, SIP’s flexibility and simpler message format give it an advantage for diverse codec support.

📖 Explanation: A larger GOP means more frames depend on earlier reference frames; when a reference frame is corrupted, the error spreads to a greater number of subsequent frames, amplifying visual degradation. Hence, increasing GOP size typically worsens error propagation.

📖 Explanation: Real‑time games require low latency; codecs that achieve very high compression often need intensive transforms and motion analysis, which can introduce processing delays. Designers must balance the desire for small bandwidth against the need for fast encoding, making the complexity‑induced latency the critical factor.

📖 Explanation: The SR contains transmission timestamps and packet counts, helping the sender estimate available bandwidth, while the RR conveys packet loss, jitter, and other quality metrics observed by the receiver. Together they enable dynamic adjustment of lossy encoder settings such as bitrate or QP.

📖 Explanation: Surveillance systems generate large volumes of video continuously. Using a lossy codec dramatically reduces file size, allowing longer retention periods on limited storage media while still preserving enough detail for typical investigative purposes, making storage efficiency the primary motivation.

📖 Explanation: Entropy coding efficiently compresses symbols but relies on the statistical redundancy created by earlier stages such as quantization and transform coding. When used together, the pipeline exploits both spatial/temporal redundancy and symbol frequency, producing a higher overall compression ratio than entropy coding by itself.

📖 Explanation: Perceptual models show that the human ear has reduced sensitivity above certain thresholds, especially in noisy environments. Consequently, lossy audio encoders discard or heavily quantize high‑frequency components to save bits while maintaining perceived quality, aligning with option A.

📖 Explanation: An adaptive client monitors the fraction‑lost field in RTCP Receiver Reports; if loss rises above a preset threshold (e.g., 5 %), the client requests a codec with a lower QP (higher quality) or higher QP (more compression) depending on policy. This dynamic switch maintains user experience under varying network conditions.

📖 Explanation: Visual masking exploits the fact that the eye is less sensitive to errors in highly textured or rapidly moving areas. Algorithms allocate fewer bits to these regions, allowing greater quantization without noticeable quality loss, thereby improving compression efficiency while preserving perceived image fidelity.

📖 Explanation: Substituting the values gives $CR = \frac{150}{45} = 3.33$, which is commonly expressed as a 3 : 1 ratio for simplicity. Therefore the nearest whole‑number answer is 3, matching option B.

📖 Explanation: Medical images demand high diagnostic fidelity, yet network constraints limit bandwidth. A hybrid scheme applies lossless compression to critical regions (e.g., lesions) while using lossy methods for less important background, achieving a manageable file size without compromising essential diagnostic information.

📖 Explanation: Rate‑distortion optimization seeks the point where increasing compression (higher QP) yields an acceptable increase in distortion while meeting bandwidth limits. Selecting a higher QP reduces the bit rate, allowing the stream to fit within the constrained channel, which exemplifies the balance described in option C.

📖 Explanation: The Content‑Type header specifies the media type and codec (e.g., audio/PCMU), enabling the receiving endpoint to interpret the payload correctly. Without this information, the receiver could not decode the media stream, making option B the accurate explanation.

📖 Explanation: When the Receiver Report shows an elevated fraction of lost packets, the control loop interprets this as network congestion and raises the QP, which reduces the bitrate and eases the load on the channel, thereby helping to preserve overall quality.

📖 Explanation: Successive video frames frequently contain only small changes; inter‑frame prediction exploits this redundancy by encoding only the differences relative to reference frames. This reduces the amount of data transmitted, which is especially effective in lossy codecs that can further quantize the residuals.

📖 Explanation: Subsampling chroma discards some color detail, which the human visual system tolerates to a degree. The result is a modest decline in color accuracy that is often acceptable for many applications, making a slight reduction the correct inference.

📖 Explanation: Jitter exceeding the packetization interval causes packets to arrive out of order more frequently. The decoder must enlarge its jitter buffer to reorder and smooth playback, leading to increased reordering handling and potentially higher latency to maintain seamless